Content, Topology and Cooperation in In-network Caching

In-network caching aims at improving content delivery and alleviating pressures on network bandwidth by leveraging universally networked caches. This thesis studies the design of cooperative in-network caching strategy from three perspectives: content, topology and cooperation, specifically focuses on the mechanisms of content delivery and cooperation policy and their impacts on the performance of cache networks. The main contributions of this thesis are twofold. From measurement perspective, we show that the conventional metric hit rate is not sufficient in evaluating a caching strategy on non-trivial topologies, therefore we introduce footprint reduction and coupling factor, which contain richer information. We show cooperation policy is the key in balancing various tradeoffs in caching strategy design, and further investigate the performance impact from content per se via different chunking schemes. From design perspective, we first show different caching heuristics and smart routing schemes can significantly improve the caching performance and facilitate content delivery. We then incorporate well-defined fairness metric into design and derive the unique optimal caching solution on the Pareto boundary with bargaining game framework. In addition, our study on the functional relationship between cooperation overhead and neighborhood size indicates collaboration should be constrained in a small neighborhood due to its cost growing exponentially on general network topologies.Verkonsisäinen välimuistitallennus pyrkii parantamaan sisällöntoimitusta ja helpottamaan painetta verkon siirtonopeudessa hyödyntämällä universaaleja verkottuneita välimuisteja. Tämä väitöskirja tutkii yhteistoiminnallisen verkonsisäisen välimuistitallennuksen suunnittelua kolmesta näkökulmasta: sisällön, topologian ja yhteistyön kautta, erityisesti keskittyen sisällöntoimituksen mekanismeihin ja yhteistyökäytäntöihin sekä näiden vaikutuksiin välimuistiverkkojen performanssiin. Väitöskirjan suurimmat aikaansaannokset ovat kahdella saralla. Mittaamisen näkökulmasta näytämme, että perinteinen metrinen välimuistin osumatarkkuus ei ole riittävä ei-triviaalin välimuistitallennusstrategian arvioinnissa, joten esittelemme parempaa informaatiota sisältävät jalanjäljen pienentämisen sekä yhdistämistekijän. Näytämme, että yhteistyökäytäntö on avain erilaisten välimuistitallennusstrategian suunnitteluun liittyvien kompromissien tasapainotukseen ja tutkimme lisää sisällön erilaisten lohkomisjärjestelmien kautta aiheuttamaa vaikutusta performanssiin. Suunnittelun näkökulmasta näytämme ensin, kuinka erilaiset välimuistitallennuksen heuristiikat ja viisaan reitityksen järjestelmät parantavat merkittävästi välimuistitallennusperformanssia sekä helpottavat sisällön toimitusta. Sisällytämme sitten suunnitteluun hyvin määritellyn oikeudenmukaisuusmittarin ja johdamme uniikin optimaalin välimuistitallennusratkaisun Pareto-rintamalla neuvottelupelin kehyksissä. Lisäksi tutkimuksemme yhteistyökustannusten ja naapurustokoon funktionaalisesta suhteesta viittaa siihen, että yhteistyö on syytä rajoittaa pieneen naapurustoon sen kustannusten kasvaessa eksponentiaalisesti yleisessä verkkotopologiassa

Beyond 5G Networks: Integration of Communication, Computing, Caching, and Control

In recent years, the exponential proliferation of smart devices with their intelligent applications poses severe challenges on conventional cellular networks. Such challenges can be potentially overcome by integrating communication, computing, caching, and control (i4C) technologies. In this survey, we first give a snapshot of different aspects of the i4C, comprising background, motivation, leading technological enablers, potential applications, and use cases. Next, we describe different models of communication, computing, caching, and control (4C) to lay the foundation of the integration approach. We review current state-of-the-art research efforts related to the i4C, focusing on recent trends of both conventional and artificial intelligence (AI)-based integration approaches. We also highlight the need for intelligence in resources integration. Then, we discuss integration of sensing and communication (ISAC) and classify the integration approaches into various classes. Finally, we propose open challenges and present future research directions for beyond 5G networks, such as 6G.Comment: This article has been accepted for inclusion in a future issue of China Communications Journal in IEEE Xplor

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

Price-Based Optimal Resource Allocation in Multi-Hop Wireless Networks

Recent advances in wireless communications and digital electronics have enabled rapid development of a variety of wireless network technologies. The undeniable popularity of wireless network is due to its ubiquity and convenience, which is appreciated by the users. In this dissertation, we study the problem of resource allocation in multihop wireless networks (so called ad hoc networks). A wireless ad hoc network consists of a collection of wireless nodes without a fixed infrastructure. Two wireless nodes communicate with each other directly, if they are within the transmission range of each other. Otherwise, the communication is achieved through the relays of intermediate nodes. Compared with traditional wireline networks, the unique characteristics of wireless networks pose fundamental challenges to the design of effective resource allocation algorithms that are optimal with respect to resource utilization and fair across different network flows. Particularly, the following issues of wireless networks need fresh treatment: (1) Interference of wireless communication. Flows not only contend at the same node (contention in the time domain), but also compete for shared channel if they are within the interference ranges of each other (contention in the spatial domain). (2) Multiple resource usage. Sending data from one wireless node to another needs to consume multiple resources, most notably wireless bandwidth and battery energy. (3) Autonomous communication entities. The wireless nodes usually belong to different autonomous entities. They may lack the incentive to contribute to the network functionality in a cooperative way. (4) Rate diversity. Wireless nodes can adaptively change the transmission bit rate based on perceived channel conditions. This leads to a wireless network with rate diversity, where competing flows within the interference range transmit at different rates. None of the existing resource allocation algorithms in wireless ad hoc networks have realistically considered end-to-end flows spanning multiple hops. Moreover, strategies proposed for wireline networks are not applicable in the context of wireless ad hoc network, due to its unique characteristics. In this dissertation, we propose a new price-based resource allocation framework in wireless ad hoc networks to achieve optimal resource utilization and fairness among competing end-to-end flows. We build our pricing framework on the notion of maximal cliques in wireless ad hoc networks, as compared to individual links in traditional wide-area wireline networks. Based on such a price-based theoretical framework, we present a two-tier iterative algorithm. Distributed across wireless nodes, the algorithm converges to a global network optimum with respect to resource allocations. Further, we present a price pair mechanism to coordinate multiple resource allocations, and to provide incentives simultaneously such that cooperation is promoted and the desired global optimal network operating point is reached by convergence with a fully decentralized self-optimizing algorithm. Such desired network-wide global optimum is characterized with the concept of Nash bargaining solution, which not only provides the Pareto optimal point for the network, but is also consistent with the fairness axioms of game theory. Finally, we present a channel aware price generation scheme to decompose the bit rate adjustment and the flow rate allocation. The allocation result achieves channel time fairness where user fairness and channel utilization is balanced. The major achievements of this dissertation are outlined as follows. It models a system-wide optimal operation point of a wireless network, and outlines the solution space of resource allocation in a multihop wireless network; It presents a price-based distributed resource allocation algorithm to achieve this global optimal point; It presents a low overhead implementation of the price-based resource allocation algorithm; It presents an incentive mechanism that enables the resource allocation algorithm when users are selfish

Reliability and Efficiency of Vehicular Network Applications

The DSRC/WAVE initiative is forecast to enable a plethora of applications, classified in two broad types of safety and non-safety applications. In the former type, the reliability performance is of tremendous prominence while, in the latter case, the efficiency of information dissemination is the key driving factor. For safety applications, we adopt a systematic approach to analytically investigate the reliability of the communication system in a symbiotic relationship with the host system comprising a vehicular traffic system and radio propagation environment. To this aim, the¬ interference factor is identified as the central element of the symbiotic relationship. Our approach to the investigation of interference and its impacts on the communication reliability departs from previous studies by the degree of realism incorporated in the host system model. In one dimension, realistic traffic models are developed to describe the vehicular traffic behaviour. In a second dimension, a realistic radio propagation model is employed to capture the unique signal propagation aspects of the host system. We address the case of non-safety applications by proposing a generic framework as a capstone architecture for the development of new applications and the efficiency evaluation of existing ones. This framework, while being independent from networking technology, enables accurate characterization of the various information dissemination tasks that a node performs in cooperation with others. As the central element of the framework, we propose a game theoretic model to describe the interaction of meeting nodes aiming to exchange information of mutual or social interests. An adaptive mechanism is designed to enable a mobile node to measure the social significance of various information topics, which is then used by the node to prioritize the forwarding of information objects

Scheduling for Large Scale Distributed Computing Systems: Approaches and Performance Evaluation Issues

Although our everyday life and society now depends heavily oncommunication infrastructures and computation infrastructures,scientists and engineers have always been among the main consumers ofcomputing power. This document provides a coherent overview of theresearch I have conducted in the last 15 years and which targets themanagement and performance evaluation of large scale distributedcomputing infrastructures such as clusters, grids, desktop grids,volunteer computing platforms, ... when used for scientific computing.In the first part of this document, I present how I have addressedscheduling problems arising on distributed platforms (like computinggrids) with a particular emphasis on heterogeneity and multi-userissues, hence in connection with game theory. Most of these problemsare relaxed from a classical combinatorial optimization formulationinto a continuous form, which allows to easily account for keyplatform characteristics such as heterogeneity or complex topologywhile providing efficient practical and distributed solutions.The second part presents my main contributions to the SimGrid project,which is a simulation toolkit for building simulators of distributedapplications (originally designed for scheduling algorithm evaluationpurposes). It comprises a unified presentation of how the questions ofvalidation and scalability have been addressed in SimGrid as well asthoughts on specific challenges related to methodological aspects andto the application of SimGrid to the HPC context

Self-organised multi-objective network clustering for coordinated communications in future wireless networks

The fifth generation (5G) cellular system is being developed with a vision of 1000 times more capacity than the fourth generation (4G) systems to cope with ever increasing mobile data traffic. Interference mitigation plays an important role in improving the much needed overall capacity especially in highly interference-limited dense deployment scenarios envisioned for 5G. Coordinated multi-point (CoMP) is identified as a promising interference mitigation technique where multiple base stations (BS) can cooperate for joint transmission/reception by exchanging user/control data and perform joint signal processing to mitigate inter-cell interference and even exploit it as a useful signal. CoMP is already a key feature of long term evolution-advanced (LTE-A) and envisioned as an essential function for 5G. However, CoMP cannot be realized for the whole network due to its computational complexity, synchronization requirement between coordinating BSs and high backhaul capacity requirement. BSs need to be clustered into smaller groups and CoMP can be activated within these smaller clusters. This PhD thesis aims to investigate optimum dynamic CoMP clustering solutions in 5G and beyond wireless networks with massive small cell (SC) deployment. Truly self-organised CoMP clustering algorithms are investigated, aiming to improve much needed spectral efficiency and other network objectives especially load balancing in future wireless networks. Low complexity, scalable, stable and efficient CoMP clustering algorithms are designed to jointly optimize spectral efficiency, load balancing and limited backhaul availability. Firstly, we provide a self organizing, load aware, user-centric CoMP clustering algorithm in a control and data plane separation architecture (CDSA) proposed for 5G to maximize spectral efficiency and improve load balancing. We introduce a novel re-clustering algorithm for user equipment (UE) served by highly loaded cells and show that unsatisfied UEs due to high load can be significantly reduced with minimal impact on spectral efficiency. Clustering with load balancing algorithm exploits the capacity gain from increase in cluster size and also the traffic shift from highly loaded cells to lightly loaded neighbours. Secondly, we develop a novel, low complexity, stable, network-centric clustering model to jointly optimize load balancing and spectral efficiency objectives and tackle the complexity and scalability issues of user-centric clustering. We show that our clustering model provide high spectral efficiency in low-load scenario and better load distribution in high-load scenario resulting in lower number of unsatisfied users while keeping spectral efficiency at comparably high levels. Unsatisfied UEs due to high load are reduced by $68.5\%$ with our algorithm when compared to greedy clustering model. In this context, the unique contribution of this work that it is the first attempt to fill the gap in literature for multi-objective, network-centric CoMP clustering, jointly optimizing load balancing and spectral efficiency. Thirdly, we design a novel multi-objective CoMP clustering algorithm to include backhaul-load awareness and tackle one of the biggest challenges for the realization of CoMP in future networks i.e. the demand for high backhaul bandwidth and very low latency. We fill the gap in literature as the first attempt to design a clustering algorithm to jointly optimize backhaul/radio access load and spectral efficiency and analyze the trade-off between them. We employ 2 novel coalitional game theoretic clustering methods, 1-a novel merge/split/transfer coalitional game theoretic clustering algorithm to form backhaul and load aware BS clusters where spectral efficiency is still kept at high level, 2-a novel user transfer game model to move users between clusters to improve load balancing further. Stability and complexity analysis is provided and simulation results are presented to show the performance of the proposed method under different backhaul availability scenarios. We show that average system throughout is increased by 49.9% with our backhaul-load aware model in high load scenario when compared to a greedy model. Finally, we provide an operator's perspective on deployment of CoMP. Firstly, we present the main motivation and benefits of CoMP from an operator's viewpoint. Next, we present operational requirements for CoMP implementation and discuss practical considerations and challenges of such deployment. Possible solutions for these experienced challenges are reviewed. We then present initial results from a UL CoMP trial and discuss changes in key network performance indicators (KPI) during the trial. Additionally, we propose further improvements to the trialed CoMP scheme for better potential gains and give our perspective on how CoMP will fit into the future wireless networks