Globecom 2013 Workshop - Management of Emerging Networks and Services Program

This paper is standardization oriented paper that describes the SDN (Software-Driven Networking) Enablers in the ETSI AFI GANA Reference Model for Autonomic Management & Control (an emerging standard from ETSI), and impact of Virtualization. This is because in this study we see that Autonomic Management & Control and SDN (Software-Driven Networking) share the same objective of enabling programmable, manageable, dynamically self-adaptable and cost-effective networks and services. (1) Modularization of Logically centralized Control Software (GANA Network Level DEs in the GANA Knowledge Plane) and Reference Points Definitions; (2) Primitives for Programmability at various layers; (3) Run-time Executable Behavioral Models to complement Policy-Control with dynamic policies; (4) The role and value the GANA MBTS (Model Based Translation Service) brings in SDN; (5) The role and value the GANA ONIX (Overlay Network for Information eXchange) brings in SDN; (6) Interworking GANA Knowledge Plane Decision Elements and OpenFlow-based Controllers. The study is important because it is now becoming critical to study and explore the relationships between Autonomic Management & Control and SDN enabling frameworks, as well as Virtualization, identify complementarities between the paradigms and close the gaps by unifying SDN concepts and associated frameworks with the emerging ETSI AFI GANA Reference Model standard for Autonomic Networking, Cognitive Networking and Self-Management.

Nowadays, one of the main problems of mobile operators is to handle network traffic more resourcefully. Techniques, which increase the traffic capacity over the mobile core with minimum costs, play a fundamental role. Following advent of smart phones, the most of the traffic bandwidth is being used for connecting to external IP networks, like the Internet. Consequently, this overloaded traffic causes congestion over the mobile core network and degrade the quality of service. In this regard, we suggest a process using recently revealed switching system (OpenFlow), to balance the traffic over the mobile core network and use resources more efficiently. In this paper, we imply a technique to decrease the core network load using this switching system and provide a better quality of service for specific services over 3G and Evolved Packet Core (EPC). Mobile Operators with the proposed solution may save millions of dollars per year.

Software-Defined Networking (SDN) is a new paradigm, which emerged in the innovation for future networks and has been successfully applied in many scenarios including Campus/Enterprise network and Data Center network. By extending the concept of SDN and autonomicity to the design of versatile network infrastructures, especially to the design of a carrier grade network, we propose AMA, which is an autonomic management architecture for SDN-based multi-service network. AMA is designed and implemented by utilizing autonomic management and network virtualization technologies. We believe that AMA can support more application types, and can be used to build a more flexible network.

The increase in complexity of computer networks and their services have boosted the development of standardizations, models and solutions for network management over the years. Lately, the Distributed Management Task Force (DMTF) defined the Common Information Model (CIM) for describing computational entities and businesses on the Internet. This paper proposes an extension of the CIM for Software-Defined Networking (SDN) by adding new elements (Controllers, Apps, Slices and others). Furthermore, we define a metamodel to help the process of creating and understanding the proposed model. The proposal was validated by creating a script that generates the FlowVisor configuration file using the network model as input and using Object Constraint Language (OCL) to find inconsistencies in the network.

Software Defined Networking (SDN) has already gained enormous momentum in the industry. Its innovation architecture that separates the control and forwarding planes allow third-party developers more leeway in how a network behaves. Since new protocols and forwarding schemes are needed to produce better network performance, efforts have been put forth in redefining user-defined protocol support. Besides, the concept of autonomicity has been proposed recently to solve the dilemma of management in complex network environments. In this paper, we propose the design and implementation of PindSwitch, which provides a SDN-based Protocol-independent platform to allow users to outline their own protocols' format and flow processing rules into physical switches. We also introduce autonomicity and self-* attributes into SDN by extending the architecture of GANA to achieve better management of user-defined protocols and their processing schemes.

Dense and large scale Wireless Sensor Networks (WSNs) require efficient data gathering strategies that are robust, scalable, cover large areas, and extend network lifetime. We propose EDGS as novel and efficient data gathering algorithm to collect data from these challenging WSNs. EDGS creates virtual network backbone based on the Gray Cube regular graph structure. EDGS collects data in parallel short paths, balances energy consumption, and is highly tolerant against sensor failures. The backbone construction is adaptive with good connectivity, low network diameter, and short average path length. We present several versions of EDGS for constructing the backbone using top-down or bottom-up techniques and centralized or distributed approaches. The backbone sensors act as access points for non backbone sensors for local data collection. We conduct comparative study using modeling techniques and NS-2 simulation to demonstrate EDGS's efficiency and its superiority compared to other recently proposed data gathering techniques in terms of energy consumption, gathering delay, scalability, QoS requirements, and fault tolerance.

The conception of the Smart Grid (SG) paradigm is to offer many benefits to the transmission, distribution, and consumption of energy. One catalyzer ingredient of the SG repertoire of changes is the idea of microgrids. As a new low voltage distribution subsystem, microgrids are expected to improve reliability, help integrate distributed resources, isolate power disturbances, and ameliorate load and supply balance. In this paper, we study a microgrid power scheduling problem with renewable sources and energy storage where five different classes of appliances are prioritized by smart meters. A novel formulation and solution based on mixed integer programming are proposed. Preliminary simulations show the efficacy of the optimization to schedule power among users and appliances of a microgrid in terms of the total power consumed and the number of power usage requests accepted by the system.

With the continuous evolution of wireless technologies, there is today a plethora of access networks ranging from wireless hotspots to high speed cellular networks. Within this rich environment and with multimodal terminals that are able to connect to different wireless technologies at once, users are expecting to benefit from higher throughput and enhanced QoS. However, the coexistence of several wireless systems rises different technical challenges including interface selection, packet scheduling, multi-path routing and mobility management. At the network level, recent protocols such as MTCP and mSCTP allow session continuity and offer the possibility of seamlessly adapting IP routing during a transmission session. These protocols are mainly based on the use of a set of IP addresses that can be associated to the same terminal and user session. But at the access level, efficient packet scheduling mechanisms on multiple interfaces are still required. New rules and approaches are needed to select the most suitable technology that better fits QoS requirements considering the dynamic mobile user environment. In addition, optimizing energy consumption should also be considered in order to lengthen mobile terminals' battery lifetime. In this paper we propose an energy efficient cross layer scheduling mechanism for multi-homed wireless terminals. The proposed algorithm goes through the use of energy models for both 802.11n and LTE technologies to dynamically select the more suited technology according to users' context. Performance evaluations of the proposed algorithm are presented and discussed. They show that a significant energy saving can be achieved while respecting applications QoS requirement.

Machine-to-Machine (M2M) networks must be energy-efficient to operate autonomously for years, or even decades. In this paper, we consider a synchronized duty-cycled M2M network composed of a huge number of dormant devices that periodically wake up to transmit data to a coordinator. We propose the use of Distributed Queuing (DQ) tree-splitting algorithms to optimize the shared access to the channel among the high number of devices, in order to improve the energy efficiency and thus extend the network lifetime. We evaluate the energy performance of DQ access in this kind of dense M2M networks, and we compare it to traditional access schemes based on variations of Frame Slotted-ALOHA (FSA) and the Contention Tree Algorithm (CTA). Computer-based simulations show that DQ can reduce the energy consumption in more than a 50% with respect to FSA and CTA. Results show that there is an optimum number of contention slots which maximizes the energy efficiency of DQ regardless of the number of devices. The performance evaluation presented in this paper also compares the energy consumption of DQ using low power Wi-Fi and IEEE 802.15.4 devices.

Wireless Sensor Networks (WSNs) have become increasingly popular in recent years for controlling systems where human intervention is undesirable or impossible. The main challenges in designing and planning the operations WSNs are to optimize the energy consumption of sensor nodes and prolong the network lifetime. Hierarchical routing protocols are proven to be efficient to drastically reduce the energy consumption and prolong the lifespan of the network. For example, Energy-Aware Evolutionary Routing Protocol (EAERP) is an Evolutionary Algorithm (EA) based routing protocol that aims to achieve a better compromise between the stability time and network lifetime. This paper reformulates the design of EAERP according to the sensing model. Specifically, disc (isotropic) and probabilistic sensing model are considered. Moreover, for further extension of network lifetime a novel wake-up scheduling scheme applied to alternate between active and idle state of sensor nodes. Extensive simulations are performed for each of sensing models and results show that the proposed protocol improves the energy efficiency and network lifetime.

Attempts by the research community to meet expectations arising from future Internet systems, and specifically to provide Quality of Service (QoS) for multimedia multi-user sessions, have resulted in mechanisms such as Multi-User Aggregated Resource Allocation (MARA). Its results have been promising, mainly because it drastically reduces signaling and processing overhead, despite its limitations in multi-ingress scenarios. In view of these benefits, this paper proposes the Multi-User Aggregated Resource Allocation - Multi-Ingress to overcome the main limitations of MARA so that it can serve as a promising tool in todays and future IP-based network systems. The simulation experiments carried out for MARA-MI demonstrated the benefits in optimizing bandwidth use and networking costs while maintaining QoS over time in multiple sessions, in comparison to a relevant related work.

With the mobile network core evolving towards an unlayered and decentralized architecture, distributed mobility management appears to be more compatible and efficient with the flattened networks. In this paper, we propose a new approach to realize the distributed mobility management using the software defined networking techniques instead of the existing mobility management protocols. The mobility management functions are implemented with the help of distributed controllers. The controllers will update the involved routing tables directly in case of handover, which realizes the route optimization inherently. The test results show that the proposed SDN-aided approach is an efficient mechanism for distributed mobility management.

The demand for efficient use of ICT resources has recently been growing. Equipment costs at datacenters have been reduced to satisfy this demand and all ICT resources have been required to be controlled on demand. Network virtualization and software defined networking (SDN) technologies have been applied to datacenter networks for the same reason. On the other hand, efficient networks and operations also need to be provided, including traditional storage systems. Ethernet fabric and I/O convergence have been applied to satisfy these requirements. However, the SDN approach has mainly been applied to local area networks and flexible control has so far not been accomplished for converged networks. We introduced an SDN approach similar to OpenFlow and applied this to Fibre Channel over Ethernet (FCoE) networks, which is a method of achieving I/O converged networks. This method of controlling flows can coexist with OpenFlow based SDN flow control.We explain the differences between our method of flow control, OpenFlow, and path optimization with FCoE and their effects as examples in this paper.

In this paper, we propose a novel cloud-based building management system (BMS) architecture for a short-term cooling load forecasting mechanism to manage the building cooling system (BCS) and reduce the cost of BCS construction and maintenance. The BCS is very important to economize on air conditioning since a huge amount of energy is consumed by the cooling system of buildings in summer and some recent work have attempted to manage the BCS using short-term cooling load forecasting. In order to have accurate forecasts, however, excellent computing systems are necessary to predict and control the BCS based on a huge amount of past energy consumption data with rapid processing speed. In the proposed architecture, hence, we use centralized computing resources and storages to predict and control the BCS. Further, we propose a model with short-term cooling load forecasting and semantic analysis system that uses data mining techniques to improve the forecasting accuracy. Through our performance results, the proposed forecasting model outperforms another scheme in terms of the forecasting accuracy to control the BCS and it is expected that the cost of the BCS maintenance will be greatly reduced with the cloud-based BMS architecture.

Large-scale centralized network management such as cloud computing, software defined network (SDN) and network virtualization are becoming popular. This requires appropriate interface devices to incorporate these new devices with legacy devices for the large-scale network management. To accommodate the existing communication devices which are not expected to manage a large network, a centralized control monitoring will be required. We propose a cache management algorithm in order to avoid the problem of increasing load by monitoring existing network equipments. We propose a Tambourine cache control method which controls Time-to-Live(TTL) in a similar way that TCP adjusts the congestion window size. This method is able to keep CPU utilization of SNMP devices below a certain value and guarantees the granularity of monitoring interval. We show this architecture can be applied with the general load balancer using content-aware switching.

Differential games are multi-agent versions of optimal control problems, which have been used for modeling control systems of smart grids. Thus, a differential-game theoretic approach is a very promising way to discuss a demand-side energy management system where there are multiple decision-making entities. This paper first indicates that the optimal demand-side management of multiple demand-side actors (e.g., consumers, houses, buildings, communities) in a decentralized way is formulated as a differential game. In addition, we point out that an information structure (e.g., open-loop, feedback), that is the most important property of differential games, corresponds to availability of communications. When information shared by communications is available, it enables demand-side actors to act in an appropriate manner, i.e., demand-side actors conduct decentralized feedback control. On the other hand, when shared information is unavailable due to communication failure, demand-side actors do not necessarily give up control and they may use another type of control, such as prediction-based control. For example, demand-side actors are assumed to manage the power consumption to minimize disutility and the electricity rates allocated to the power grid, and to maintain the demand-supply balance by considering a photovoltaic power generation. Numerical analyses demonstrate that the proposed framework enables a trade-off analysis for decentralized controls considering the availability of shared information.

Modern datacenters are becoming increasingly complex, with datacenter networks (DCN's) built to meet the data transmission demands of densely interconnected nodes of server hosts and switches. Load balancing in DCN's - to balance the bandwidth utilization among the DCN links - is indispensable for meeting important objectives such as maximizing throughput and minimizing latency. Simulation has been the de facto empirical method for investigating the stability of DCN's under load balancing policies. To complement simulation with analytical insights into load balancing stability of DCN's, in this paper, we present an application of the qualitative version of the Lyapunov stability theory for load balancing DCN's modeled as discrete-event systems. The general Lyapunov control theory states that a controlled system is stable if there exists a function on the state space of the system, called the Lyapunov function, whose value is non-increasing along any execution trajectory of the system. Analytically proving the existence of such a Lyapunov function is sufficient to verify that the DES model representing a class of DCN's under a load balancing policy is stable. We illustrate the utility of our approach by investigating the stability of a class of DCN's configured in a fat-tree topology under a specific load balancing policy. Our work represents the first step towards a general qualitative stability theory for the policy design of load balancing algorithms for DCN's.

There is a new trend to consider Distributed Mobility Management (DMM) for flat network architectures to cope with the increased distributed nature of the mobile networks. DMM improves the routing optimization and reduces the scalability issues when compared with the centralized mobility management, through the traffic anchoring distribution at the Access Routers (ARs). However, the handover optimization, which also demands for fast and soft handovers to reduce/eliminate the handover latency and the respective packet loss, is not properly addressed in the DMM. Although current seamless handover approaches, already integrated in centralized mobility schemes, could also be adapted to the DMM schemes, they introduce new entities/functionalities, messages and buffering/bicasting mechanisms to reduce the handover latency or the packet loss. In this paper, the seamless IP handover is addressed from a novel make-without-break perspective, which is able to maintain two logical connections in the same physical interface with two Access Points (APs) from distinct IP networks. The outcome of the evaluation shows that make-without-break with a DMM scheme is able to reduce or even eliminate the handover latency and the packet loss from link disconnection, providing seamless IP session continuity in mobile environments.

This paper proposes an efficient dynamic traffic allocation scheme for multi-flow distribution in LTE-WLAN heterogeneous networks, where data traffic is split into multiple sub-flows and transmitted through different networks simultaneously. The state transition equations of the M/M/1 queuing system are modified to model the parallel transmissions. To improve system performance especially in practical situations, our modified queuing system model also considers random interference and dynamic changes of available bandwidth which are often ignored in previous work. We also study the traffic characteristics to ameliorate the trade-off between limited network resources and multiple flow transmission. A novel scheme — layered video streaming allocation (LVSA) — based on traffic characteristics is proposed to increase system capacity especially in high delay situations. Simulation results indicate that our schemes have a significant improvement in delay performance and system capacity compared with other schemes.

This paper formulates a new QoS model for a tree-based cognitive radio network (CRN) which is under test for communication in mountainous areas. The model takes spectrum quality into account, which results in a more complex spectrum decision involving 3-dimension information: cognitive users, spectrums and their quality for combination optimization making. An optimal algorithm with correctness and performance proofs is proposed to search the best solution among all possible candidates. Each candidate takes a form of extreme maximal bicliques (EMB) in a viewpoint of cognitive users and spectrums, or a user-spectrum space and the best one adds more rich features to EMB. Simulations with parameters coinciding with real application requirements and experiment data from many days of experiments are conducted, showing a real-time performance of the algorithm.

This paper is standardization oriented paper that describes an Implementation Guide for an emerging standard for autonomic management &control, namely the ETSI AFI GANA Reference Model for Autonomic Networking, Cognitive Networking and Self-Management (an emerging standard from ETSI). The implementation guide also takes into consideration the impact of emerging paradigms such as SDN and Virtualization. This is because as the standardized Reference Model has been published, it becomes important to provide an associated Implementation Guide that can be followed in implementing autonomic management & control in architectures.

Some M2M applications such as those found in a Smart Grid environment generate event driven and delay sensitive uplink traffic. Wide area cellular systems such as LTE are usually not optimized for such traffic. In this paper, we design an LTE scheduler with the main objective of maximizing the percentage of uplink packets that satisfy their individual delay budgets. In order to do this accurately, we allow devices to notify the eNodeB of the age of the oldest packet in their buffers via a new MAC control element in the uplink MPDU. This information is used by the eNodeB to calculate an absolute deadline for each packet request individually, and the eNodeB scheduler ranks requests according to an urgency metric that depends upon the time remaining to the deadline and other factors such as the volume of pending data in the device buffers. Using an OPNET simulation model of an LTE TDD system, we show that our proposed scheduler can satisfy the uplink delay budget for more than 99% of packets for bursty delay sensitive M2M traffic even when the system is fully loaded with regard to the data channel utilization.

Resource allocation is one of the key issues in long term evolution (LTE) systems. In this paper, we propose an adaptive resource allocation scheme with quality of service (QoS) guarantees to maximize system throughput for high-speed mobile LTE systems. In this scheme, considering that channel quality indicator (CQI) might be changed in fast mobile scenarios which can reduce the system throughput, we first propose a novel CQI feedback method to achieve continue high throughput. Then we optimize the resource blocks (RB) allocation procedure under QoS requirements and adopt a more effective modulation and coding scheme (MCS) selection method to improve the system performances. Through extensive simulations, the results show that the proposed resource allocation scheme can achieve higher system throughput and better performance stability compared with some existing schemes in high-speed mobile LTE systems.

In SON enabled LTE networks many different SON functions may operate simultaneously in order to optimize the entire network performance. With the increasing number of SON functions the probability of conflicts and dependencies between them increases and become more challengeable to handle. In this paper an integrated approach for two SON functions, namely handover optimization and load balancing combined with admission control is presented. In this approach the conflicts are solved using the combination of Fuzzy Q-Learning Control (FQLC) algorithm and a heuristic Diff_Load algorithm. The novelty of this approach lies in using of FQLC for adjusting more than a single parameter, namely the handover hysteresis and the time to trigger. Working in parallel, the Diff_Load tunes the handover offset. The proposed approach has been evaluated using the LTE-Sim simulator.

Small cells such as femto cells are commonly being deployed for traffic offloading in heterogeneous wireless networks (HetNet), and multimode terminals designed for HetNets have the capability to simultaneously support two or more different classes of calls. A user having a multimode terminal with multiple ongoing calls that are connected through a femto cell may experience necessary handoff when the user moves outside the coverage area on the femto cell in a HetNet. However, multiple handoff calls from a multimode terminal may be dropped because none of the available candidate radio access technologies has enough residual capacity to accommodate the multiple handoff calls from the femto cells. In order to reduce the probability of dropping multiple handoff calls in HetNets, this paper proposes a handoff decision scheme that uses selective call dropping and bandwidth adaptation to decrease overall call dropping probability of multiple handoff calls. The proposed scheme uses individual call priority for performing selective call dropping. Performance of the proposed scheme is evaluated and compared for four different scenarios. Results show that the proposed scheme significantly reduces the probability of dropping essential handoff calls in HetNet.

Named Data Networking (NDN) is a clean slate Internet paradigm that embeds some security primitives in its original design, which is being considered as one of the promising candidates for next-generation Internet architecture. However, it may suffer from some emerging threats such as Interest Flooding Attacks (IFA), which means corresponding security management mechanisms need to be designed to improve its security. In this paper, we focus on the IFA that can severely consume the memory resource for the Pending Interest Table (PIT) of each involved NDN router by flooding large amount of malicious Interests with spoofed names. To loosen the stress of PIT attacked by IFA, we propose an approach called Disabling PIT Exhaustion (DPE) to divert all the malicious Interests out of PIT, by directly recording their state information (e.g., incoming interface) in the name of each malicious Interest rather than PIT, as well as introducing a packet marking scheme to enable Data packet forwarding without the help of PIT. DPE can be considered as a security management mechanism for the emerging NDN architecture, which aims at reducing memory resource consumption for each NDN router. Moreover, we present an in-depth evaluation on DPE, via extensive simulations under realistic users' behavior model. Simulation results show DPE can significantly mitigate the damage effect of IFA on exhausting PIT's memory resource. To the best of our knowledge, DPE is the first attempt to design a security management mechanism embedding with the idea "decoupling malicious Interests from PIT" to counter IFA.

With the rapid increase in deployment of smart meters across North America, utility resources such as water, gas and electricity consumption data is being collected at a much higher granular level. The huge amount of data is being used to make demand-response applications smarter. A large part of this deployment of smart utility networks and Advanced Metering Infrastructure (AMI) is being done using the wireless mesh architecture due to the low deployment costs offered by this method. Although wireless environment parameters such as fading and path loss differ widely from home, outdoor to industrial, in-building scenarios, efficient protocols at the Medium Access Control (MAC) and Physical (PHY) layers and lower layer agnostic data routing protocols can be employed to overcome these challenges. For such routing protocols to be applicable to smart utility networks, reliability and scalability are vital metrics which will determine the performance in such networks. In this paper, we analyze reliability and scalability of three such routing protocols, viz. RPL (IPv6 Routing Protocol for Low power and Lossy Networks), LOAD (6LoWPAN Ad Hoc On-Demand Distance Vector Routing) and a proprietary flavor of Geographical Routing.

Usage of multimedia communication in everyday life has seen a remarkable growth. Vast in Bandwidth demand often result in lower network performance and reduced quality of user experience during congestion. In this paper, we will address congestion control problem while providing quality of service (QOS) of delay for inelastic flows like video streaming, IPTV, etc. First, we propose an extension of an existing user utility function [2] to capture user's satisfaction over bandwidth allocation, QoS, and the cost to acquire the service. Second, we will study the relationship between these three entities.

The introduction of mobile sink to wireless sensor networks (WSNs) can effectively address the hot-spot problem. However, as the sink moves in the sensing area, its location information needs to be broadcasted periodically to ensure network connectivity. This additional location update process will increase communication cost in each sensor node. To deal with this problem, this paper proposes a Square-Based Location Update Protocol (SLUP). In SLUP, the target area is divided into squares and subdivided into virtual grids. The sink does not need to broadcast its location information to the entire network when it only moves inside a square. Besides, the pattern of sink mobility is determined by real-time network parameters, e.g., Average Residual Energy of Sensor Nodes (ARESN) and sojourn time in a square. Such controlled mobility pattern can not only decrease the probability of moving out of the current square for the sink but also achieve load balancing in the network. Simulation results demonstrate that SLUP outperforms the traditional protocols in reducing the energy consumption of location update and prolonging the network lifetime.

In this paper, we propose a novel approach for addressing both inter-cell interference and handover failure issues in dense WCDMA small cell deployments. This is achieved through an innovative scrambling allocation approach and an efficient spreading code allocation scheme that allow appropriate spatial reuse of resources. The proposed enhancements can be implemented in a centralised or distributed manner, and they are standard compliant. Simulation results show that the proposed approach can significantly mitigate inter-cell interference in both data and control channels, and thus result in enhanced network and user capacity as well as mobility management in dense small cell clusters.

Subscriber churn is a concern of customer care management for most of the mobile and wireless service providers and operators due to its associated costs. This paper explains our work on subscriber churn analysis and prediction for such services. We work on data mining techniques to accurately and efficiently predict subscribers who will change-and-turn (churn) to another provider for the same or similar service. The dataset we use is a public and real dataset compiled by Orange Telecom for the KDD 2009 Competition. Number of teams achieved high scores on this dataset requiring a significant amount of computing resources. We are aiming to find alternative methods that can match or improve the recorded high scores with more efficient and practical use of resources. In this study, we focus on ensemble of meta-classifiers which have been studied individually and chosen according to their performances.

XML has become a standard widely used in wireless networking technologies to improve flexibility and interoperability between heterogeneous applications. However, applying this technology to areas such as network management across a wireless embedded internet can pose significant challenges due to the verbosity of XML. A number of compression techniques and tools have been applied to this problem to help transform highly-structured data into a more compact form. Despite this choice, there is a lack of support for tools which are optimised for embedded computing. In this paper we will show the performance trade-offs that exist when compression is applied using different techniques. Furthermore, we will describe a tool which has been specially designed to be used within the domain of network management within a constrained environment.

The dissemination of information in wireless networks is a fundamental aspect in several network processes, such as routing, monitoring and management. Nowadays, most of the techniques for dissemination of management information adopt controlled flooding approaches, which usually impairs the network performance. In this sense, the optimization of the dissemination of management information for large-scale wireless scenarios remains a relevant research challenge. In this paper, it is presented and analyzed the performance of the Neighbors Eyesight Direction (NED) dissemination against to OSPF, uncontrolled flooding and Gossip approaches in wired and large network scenarios. NED is able to work on wired and large-scale wireless scenarios, showing to be more efficient than the baseline approaches. With lower dissemination cost and lesser recursive cycles, NED proved to be scalable to disseminate management information for scenarios with a large number of devices.

The increase of digital data between content's servers and clients in a network causes congestion problems when downloading big web contents including files, streaming media, etc. Content Delivery Network (CDN) is introduced to overcome such problems by redirecting client's request to a nearest server. However, with intensity increasing number of people accessing internet, the performance of CDN is reduced and sometimes congested. We propose an architecture to solve such problems with a new management method to redirect client's request through a router. This method is more effective than the traditional DNS-based redirection that is currently being used. We introduce a special router named as Service-oriented Router (SoR) that can perform a deep packet inspection (DPI) into the packet streams. Our experiment conducted with both analytical modeling as well as test bed experiments which confirmed that the router-based request redirection management reduced the response time by 23.3% and test bed RTT 7.7% compared to the DNS-based request redirection management.

In this paper we present the role of SDL in the recently emerged and growing domain of autonomic systems engineering, in which SDL has a role to play. The topic and issues discussed in this paper are important because the subject of the role of SDL in autonomic systems engineering has not yet been explored due to the fact the area of autonomic systems engineering is still a growing even though it is now a mature area. In this paper we investigate the role SDL should play in autonomic systems engineering. At the same time we raise a series of questions we believe both the research community and the industry at large needs to consider in this context and come up with solutions that will solidify the role of SDL in such emerging domains. While we provide important insights, the goal is not to provide answers to each of the questions we raise in this study, but rather to discuss issues that both academia and industry should seize within this growing area. The domain of Autonomic Networking is now seeing a Reference Model that defines the associated concepts of the domain, their relationships and constraints, being developed in ETSI - European Telecommunications Standards Institute. Thus, in this paper, we argue the need for the formalization of the Reference Model as a standardizable Meta-Model and present the role of SDL in a model-driven systems engineering methodology and associated tool-chain for designing stable autonomic systems.

This paper discusses the ETSI AFI (Autonomic network engineering for the self-managing Future Internet) dedicated scenario for the deployment of Autonomic Cooperative Behaviour (ACB) for the needs of the instantiation of Autonomicity Enabled Ad-hoc and Mesh Network Architecture. An inherent feature of ACB is the use of cooperative data processing and computing among network devices for the purposes of improving the related system robustness and dependability. In fact, as much as they may be differentiated, both ad-hoc and mesh networks share certain common aspects allowing for the application of the assumed scenario in the case o each of them. This approach aims to guarantee certain level of unification in terms of standardisation and validation, especially that the scenario is very demanding due to the existence of numerous walls impeding the quality of data transmission and, thus, calling for ACB as a remedy.

The Publish-Subscribe Internet Technology (PURSUIT) project aims at developing a new internetworking architecture for the Future Internet. The internetworking architecture of PURSUIT has adopted a Publish-Subscribe Internet (PSI) architecture that is one of the most promising approaches to solve the current Internet's limitations including mobility support. In this paper, a new mobility support scheme is introduced to provide better handover performance for the PSI architecture. In the proposal, a branching point in a network is dynamically selected as a proxy to support seamless handover. The proxy duplicates packets (i.e., contents) from a content source to a new attachment point of a subscriber. Numerical results show that the proposed scheme provides better handover performance compared to that of the basic PSI architecture in terms of handover latency. The required handover preparation time and signaling cost of the proposed scheme are also analyzed objectively.

Large availability of digital data, or else Big Data, offers to data scientists the chance of exploiting them and building knowledge on different aspects of everyday life related to e.g., people preferences and habits, transportation, health systems, telecommunications etc. This study targets to exploit this opportunity in the telecommunications era. Towards this direction, the paper presents the architectural aspects, the role and the foundation of the functionalities of the knowledge functional block. Knowledge functional block comprises of knowledge building mechanisms that learn different aspects of future wireless networks in order to enhance their decisions and thus their functionality. These aspects may involve context, efficiency of the decisions, energy efficiency, trust and others. Data that can be directly monitored from an Evolved Universal Terrestrial Radio Access Network (E-UTRAN) are identified and modeled to guide the input that can be used for the knowledge building mechanisms of the block.

This paper investigates the asymptotic throughput performance of common data delivery in cognitive radio networks (CRNs). Three schemes, named unicast, conventional multicast (CM) and Multiple Description Coding Multicast (MDCM), are compared by utilizing extreme value theory. The distributions of effective signal-to-noise-ratio (SNR) for unicast and CM belong to Domain of Attraction of Gumbel distribution for maxima and Domain of Attraction of Weibull distribution for minima, respectively. Based on asymptotic distribution of a central order statistic, the asymptotic performance of MDCM is then investigated. We first formulate it as an optimization problem, and then transform it into an equivalent one and solve it efficiently. By both theoretic derivation and simulation analysis, it is found that when the multicast group size grows, the per-user throughput of both unicast and CM decays to zero rapidly, while that of MDCM approaches to a positive constant, which implies that MDCM is a more promising scheme for common information delivery in CRNs considering that the number of users is typically large in CRNs.