Completion Delay Minimization For Instantly Decodable Network Coding
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| Author | : Sameh Sorour |
| Publisher | : |
| Total Pages | : 422 |
| Release | : 2011 |
| Genre | : |
| ISBN | : 9780494776438 |
Instantly Decodable Network Coding (IDNC) is a subclass of opportunistic network coding that has numerous desirable properties for a wide spectrum of applications, namely its faster decoding delay, simpler coding and decoding processes, and no decoding buffer requirements. Nonetheless, IDNC suffers from two main problems that may limit its attractiveness, as an implementable solution in future wireless networks, against full network coding (FNC), widely studied in the literature. First, it cannot guarantee the decoding of a new packet at each receiver in each transmission, which may severely affect its completion delay. Second, it requires full feedback in order to operate properly, which may be prohibitive for several practical network settings.To study the effect of feedback reduction, we formulate the completion delay minimization problem, for the cases of intermittent and lossy feedback, as extended SSP and partially observable SSP problems, respectively. We show that these new formulations have the same structure of the original SSP. We thus extend the designed algorithms to operate in intermittent and lossy feedback scenarios, after taking update decisions on the attempted and un-acknowledged packets. These redesigned algorithms are shown to achieve tolerable degradation for relatively low feedback frequencies and high feedback loss rates. iiiIn this thesis, we aim to reduce the effect of these drawbacks by studying the problems of minimizing the IDNC completion delay in full and limited feedback scenarios. Since completion delay cannot be optimized only through local decisions in each of the transmissions, we first study the evolution of the IDNC coding opportunities and determine the strategies maximizing them, not only for one transmission, but for all future transmissions. We then formulate the completion delay problem as a stochastic shortest path (SSP) problem, which turns out to be of extremely large dimensions that makes its optimal solution intractable. Nonetheless, we exploit the structure of this SSP and the evolution of the coding opportunities to design efficient algorithms, which outperform FNC in most multicast scenarios and achieve a near-optimal performance in broadcast scenarios. However, since FNC still outperforms IDNC in some network scenarios, we design an adaptive selection algorithm that efficiently selects, between these two schemes, the one that achieves the smaller completion delay.
| Author | : Mohammad Shahedul Karim |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2017 |
| Genre | : |
| ISBN | : |
The network coding paradigm enhances transmission efficiency by combining information flows and has drawn significant attention in information theory, networking, communications and data storage. Instantly decodable network coding (IDNC), a subclass of network coding, has demonstrated its ability to improve the quality of service of time critical applications thanks to its attractive properties, namely the throughput enhancement, delay reduction, simple XOR-based encoding and decoding, and small coefficient overhead. Nonetheless, for point to multi-point (PMP) networks, IDNC cannot guarantee the decoding of a specific new packet at individual devices in each transmission. Furthermore, for device-to-device (D2D) networks, the transmitting devices may possess only a subset of packets, which can be used to form coded packets. These challenges require the optimization of IDNC algorithms to be suitable for different application requirements and network configurations. In this thesis, we first study a scalable live video broadcast over a wireless PMP network, where the devices receive video packets from a base station. Such layered live video has a hard deadline and imposes a decoding order on the video layers. We design two prioritized IDNC algorithms that provide a high level of priority to the most important video layer before considering additional video layers in coding decisions. These prioritized algorithms are shown to increase the number of decoded video layers at the devices compared to the existing network coding schemes. We then study video distribution over a partially connected D2D network, where a group of devices cooperate with each other to recover their missing video content. We introduce a cooperation aware IDNC graph that defines all feasible coding and transmission conflictfree decisions. Using this graph, we propose an IDNC solution that avoids coding and transmission conflicts, and meets the hard deadline for high importance video packets. It is demonstrated that the proposed solution delivers an improved video quality to the devices compared to the video and cooperation oblivious coding schemes. We also consider a heterogeneous network wherein devices use two wireless interfaces to receive packets from the base station and another device concurrently. For such network, we are interested in applications with reliable in-order packet delivery requirements. We represent all feasible coding opportunities and conflict-free transmissions using a dual interface IDNC graph. We select a maximal independent set over the graph by considering dual interfaces of individual devices, in-order delivery requirements of packets and lossy channel conditions. This graph based solution is shown to reduce the in-order delivery delay compared to the existing network coding schemes. Finally, we consider a D2D network with a group of devices experiencing heterogeneous channel capacities. For such cooperative scenarios, we address the problem of minimizing the completion time required for recovering all missing packets at the devices using IDNC and physical layer rate adaptation. Our proposed IDNC algorithm balances between the adopted transmission rate and the number of targeted devices that can successfully receive the transmitted packet. We show that the proposed rate aware IDNC algorithm reduces the completion time compared to the rate oblivious coding schemes.
| Author | : Sergey Yurish |
| Publisher | : Lulu.com |
| Total Pages | : 396 |
| Release | : 2018-01-17 |
| Genre | : Technology & Engineering |
| ISBN | : 8469789945 |
The 1st volume of new 'Advances in Networks, Security and Communications: Reviews' Book Series contains 15 chapters submitted by 42 contributors from 13 countries. The book is divided into 3 parts: Networks, Security and Communication. The book provides focused coverage of these 3 main technologies. Chapters are written by experts in the field and address the immediate and long-term challenges in the authors' respective areas of expertise. Coverage includes wireless sensor network routing improvement; connectivity recovery, augmentation and routing in wireless Ad Hoc networks; advanced modeling and simulation approach for the sensor networks management; security aspects for mobile agent and cloud computing; various communication aspects and others. This book ensures that readers will stay at the cutting edge of the field and get the right and effective start point and road map for the further researches and developments.
| Author | : Jiankun Hu |
| Publisher | : Springer |
| Total Pages | : 403 |
| Release | : 2018-05-08 |
| Genre | : Computers |
| ISBN | : 3319907751 |
This book constitutes the refereed post-conference proceedings of the 9th International Conference on Mobile Networks and Management, MONAMI 2017, held in Melbourne, Australia, in December 2017. The 30 revised full papers were carefully reviewed and selected from 43 submissions. The papers handle topics in the area of mobile computing, wireless networking and management.
| Author | : Junwei Su |
| Publisher | : |
| Total Pages | : 33 |
| Release | : 2017 |
| Genre | : |
| ISBN | : |
"Network coding is a network layer technique to improve transmission efficiency. Coding packets is especially beneficial in a wireless environment where the demand for radio spectrum is high. However, to fully realize the benefits of network coding two challenging issues that must be addressed are: (1) Guaranteeing separation of coded packets at the destination, and (2) Mitigating the extra coding/decoding delay. If the destination has all the needed packets to decode a coded packet, then separation failure can be averted. If the scheduling algorithm considers the arrival time of coding pairs, then the extra delay can be mitigated. In this paper, we develop a network coding method to address these (decoding and latency) issues for multi-source multi-destination unicast and multicast sessions. We use linear programming to find the most efficient coding design solution with guaranteed decodability. To reduce network delay, we develop a scheduling algorithm to minimize the extra coding/decoding delay. Our coding design method and scheduling algorithm are validated through experiments. Simulation results show improved transmission efficiency and reduced network delay"--Abstract, page iii.
| Author | : Daniel Enrique Lucani |
| Publisher | : |
| Total Pages | : 196 |
| Release | : 2010 |
| Genre | : |
| ISBN | : |
Delay is a fundamental problem of data communication and networks, a problem that is not usually addressed in classical coding, information or networking theory. We focus on the general problem of delay challenged networks. This delay challenge may be related to different reasons, for example, 1) large latency, which can affect the performance of the system in delay, throughput or energy efficiency, 2) half-duplex constraints on the nodes, which precludes a node to receive and transmit at the same time, and/or 3) application-level requirements for reliable, fast and efficient dissemination of information. We consider three main problems of study and the role of network coding on solving these problems. The first is related to the problem of reliable communication in time-division duplexing channels, also known as half-duplex channels, in the presence of large latency. In large latency channels, feedback about received packets may lag considerably the transmission of the original packets, limiting the feedback's usefulness. Moreover, the time duplex constraints may entail that receiving feedback may be costly. In this work, we consider tailoring feedback and (network) coding jointly in such settings to reduce the mean delay for successful in order reception of packets. We find that, in certain applications, judicious choices provide results that are close to those that would be obtained with a full-duplex system. The second part of this thesis studies the problem of data dissemination in arbitrary networks. In particular, we study the problem of minimizing the delay incurred in disseminating a finite number of data packets. We show that the optimal solution to the problem can be thought of as a scheduling problem, which is hard to solve. Thus, we consider the use of a greedy linear network coding algorithm that only takes into account the current state of the system to make a decision. The proposed algorithm tries to maximize the impact on the network at each slot, i.e., maximize the number of nodes that will benefit from the coded packet sent by each active transmitter. We show that our scheme is considerably better, in terms of the number of slots to complete transmission, than schemes that choose the node with more information as the transmitter The third part of this work studies the case of underwater acoustic networks as an example of delay challenged networks. We consider the use of network coding under two different lights. First, as a means to obtain a lower bound on the transmission power of multicast connections in underwater networks. Second, to develop practical schemes useful in such networks. Finally, we study upper bounds on the transport capacity of underwater acoustic networks under unicast connections. We show that the amount of information that can be exchanged by each source-destination pair in underwater acoustic networks goes to zero as the number of nodes n goes to infinity. This occurs at least at a rate n-1/Qe-Wo(O(n-k)) where Wo represents the branch zero of the Lambert W function, and a path loss exponent of a. Note that typical values of the path loss exponent are a E [1, 2] for underwater acoustic networks. This is significantly different to the a> 2 of radio wireless applications.
| Author | : S. M.ostafa Mostafavi |
| Publisher | : |
| Total Pages | : |
| Release | : 2010 |
| Genre | : |
| ISBN | : |
| Author | : Mohammad Esmaeilzadeh Fereydani |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2016 |
| Genre | : |
| ISBN | : |
Over the past decade, network coding (NC) has emerged as a new paradigm for data communications and has attracted much popularity and research interest in information and coding theory, networking, wireless communications and data storage. Random linear NC (RLNC) is a subclass of NC that has shown to be suitable for a wide range of applications thanks to its desirable properties, namely throughput-optimality, simple encoder design and efficient operation with minimum feedback requirements. However, for delay-sensitive applications, the mentioned advantages come with two main issues that may restrict RLNC usage in practice. First is the trade-off between the delay and throughput performances of RLNC, which can adversely affect the throughput-optimality of RLNC and hence the overall performance of RLNC. Second is the usage of feedback, where even if feedback is kept at minimum it can still incur large amount of delay and thus degrade the RLNC performance, if not optimized properly. In this thesis, we aim to investigate these issues under two broad headings: RLNC for applications over time division duplexing (TDD) channels and RLNC for layered video streaming. For the first class of problems, we start with the reliable broadcast communication over TDD wireless channels with memory, in the presence of large latency. Considering TDD channels with large latency, excessive use of feedback could be costly. Therefore, joint optimization of feedback rate and RLNC parameters has been studied previously for memoryless channels to minimize the average transmission time for such settings. Here, we extend the methodology to the case of channels with memory by benefiting from a Gilbert-Elliot channel model. It is demonstrated that significant improvement in the performance could be achieved compared to the scheme which is oblivious to the temporal correlations in the erasure channels. Then, keeping our focus on network coded TDD broadcast systems with large latency, we consider delay sensitive applications and study the issue of throughput and packet drop rate (PDR) optimization as two performance metrics when the transmission time is considered fixed. We propose a systematic framework to investigate the advantage of using feedback by comparing feedback-free and feedback schemes. Furthermore, the complicated interplay of the mean throughputs and PDRs of users with different packet erasure conditions is discussed. Then, to better analyze the throughput performance of the proposed feedback-free scheme, we formulate the probability and cumulative density functions of users' throughputs and utilize them to investigate the problem of guaranteeing the quality of service. Finally, it is shown that the optimized feedback-free RLNC broadcast scheme works close enough to an idealistic RLNC scheme, where an omniscient sender is assumed to know the reception status of all users immediately after each transmission. For the second class of problems, we consider transmitting layered video streams over heterogeneous single-hop wireless networks using feedback-free RLNC. For the case of broadcasting single video stream, we combine RLNC with unequal error protection and our main purpose is twofold. First, to systematically investigate the benefits of the layered approach in servicing users with different reception capabilities. Second, to study the effect of not using feedback, by comparing feedback-free schemes with idealistic full-feedback schemes. To this end, we consider a content-independent performance metric and propose a general framework for calculation of this metric, which can highlight the effect of key parameters of the system, video and channel. We study the effect of number of layers and propose a scheme that selects the optimum number of layers adaptively to achieve the highest performance. Assessing the proposed schemes with real H.264 test streams, the trade-offs among the users' performances are discussed and the gain of adaptive selection of number of layers to improve the trade-offs is shown. Furthermore, it is observed that the performance gap between the proposed feedback-free scheme and the idealistic scheme is small and the adaptive selection of number of video layers further closes the gap. Finally, we extend the problem of layered video streaming to the case of transmitting multiple independent layered video streams and demonstrate the gain of coding across streams (i.e., inter-session RLNC) over coding only within streams (i.e., intra-session RLNC).
| Author | : Solairaja Ramasamy |
| Publisher | : |
| Total Pages | : |
| Release | : 2012 |
| Genre | : |
| ISBN | : |
Wireless technology has become an increasingly popular way to gain network access. Wireless networks are expected to provide efficient and reliable service and support a broad range of emerging applications, such as multimedia streaming and video conferencing. However, limited wireless spectrum together with interference and fading pose signi cant challenges for network designers. The novel technique of network coding has a significant potential for improving the throughput and reliability of wireless networks by taking advantage of the broadcast nature of wireless medium. Reverse carpooling is one of the main techniques used to realize the benefits of network coding in wireless networks. With reverse carpooling, two flows are traveling in opposite directions, sharing a common path. The network coding is performed in the intermediate (relay) nodes, which saves up to 50% of transmissions. In this thesis, we focus on the scheduling at the relay nodes in wireless networks with reverse carpooling. When two packets traveling in opposite directions are available at the relay node, the relay node combines them and broadcasts the resulting packet. This event is referred to as a coding opportunity. When only one packet is available, the relay node needs to decide whether to wait for future coding opportunities, or to transmit them without coding. Though the choice of holding packets exploits the positive aspects of network coding, without a proper policy in place that controls how long the packets should wait, it will have an adverse impact on delays and thus the overall network performance. Accordingly, our goal is to find an optimal control strategy that delicately balances the tradeoff between the number of transmissions and delays incurred by the packets. We also address the fundamental question of what local information we should keep track of and use in making the decision of of whether to transmit uncoded packet or wait for the next coding opportunity. The available information consists of queue length and time stamps indicating the arrival time of packets in the queue. We could also store history of all previous states and actions. However, using all this information makes the control very complex and so we try to find if the overhead in collecting waiting times and historical information is worth it. A major contribution of this thesis is a stochastic control framework that uses state information based on what can be observed and prescribes an optimal action. For that, we formulate and solve a stochastic dynamic program with the objective of minimizing the long run average cost per unit time incurred due to transmissions and delays. Subsequently, we show that a stationary policy based on queue lengths is optimal, and the optimal policy is of threshold-type. Then, we describe a non-linear optimization procedure to obtain the optimal thresholds. Further, we substantiate our analytical ndings by performing numerical experiments under varied settings. We compare systems that use only queue length with those where more information is available, and we show that optimal control that uses only the queue length is as good as any optimal control that relies on knowing the entire history.
| Author | : Raymond W. Yeung |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 592 |
| Release | : 2008-09-10 |
| Genre | : Computers |
| ISBN | : 0387792333 |
This book is an evolution from my book A First Course in Information Theory published in 2002 when network coding was still at its infancy. The last few years have witnessed the rapid development of network coding into a research ?eld of its own in information science. With its root in infor- tion theory, network coding has not only brought about a paradigm shift in network communications at large, but also had signi?cant in?uence on such speci?c research ?elds as coding theory, networking, switching, wireless c- munications,distributeddatastorage,cryptography,andoptimizationtheory. While new applications of network coding keep emerging, the fundamental - sults that lay the foundation of the subject are more or less mature. One of the main goals of this book therefore is to present these results in a unifying and coherent manner. While the previous book focused only on information theory for discrete random variables, the current book contains two new chapters on information theory for continuous random variables, namely the chapter on di?erential entropy and the chapter on continuous-valued channels. With these topics included, the book becomes more comprehensive and is more suitable to be used as a textbook for a course in an electrical engineering department.
