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Abhishek Sinha

Bio: Abhishek Sinha is an academic researcher from Indian Institute of Technology Madras. The author has contributed to research in topics: Network packet & Wireless network. The author has an hindex of 12, co-authored 56 publications receiving 903 citations. Previous affiliations of Abhishek Sinha include Jadavpur University & Qualcomm.

Papers published on a yearly basis

Papers
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Journal ArticleDOI
TL;DR: In this article, the authors consider a wireless broadcast network with a base station sending time-sensitive information to a number of clients through unreliable channels and formulate a discrete-time decision problem to find a transmission scheduling policy that minimizes the expected weighted sum AoI of the clients in the network.
Abstract: In this paper, we consider a wireless broadcast network with a base station sending time-sensitive information to a number of clients through unreliable channels. The Age of Information (AoI), namely the amount of time that elapsed since the most recently delivered packet was generated, captures the freshness of the information. We formulate a discrete-time decision problem to find a transmission scheduling policy that minimizes the expected weighted sum AoI of the clients in the network. We first show that in symmetric networks, a greedy policy, which transmits the packet for the client with the highest current age, is optimal. For general networks, we develop three low-complexity scheduling policies: a randomized policy, a Max-Weight policy and a Whittle’s Index policy, and derive performance guarantees as a function of the network configuration. To the best of our knowledge, this is the first work to derive performance guarantees for scheduling policies that attempt to minimize AoI in wireless networks with unreliable channels. Numerical results show that both the Max-Weight and Whittle’s Index policies outperform the other scheduling policies in every configuration simulated, and achieve near optimal performance.

379 citations

Proceedings ArticleDOI
16 Apr 2018
TL;DR: This paper develops three low-complexity transmission scheduling policies that attempt to minimize AoI subject to minimum throughput requirements and evaluates their performance against the optimal policy, and develops a randomized policy, a Max-Weight policy and a Whittle's Index policy.
Abstract: Age of Information (AoI) is a performance metric that captures the freshness of the information from the perspective of the destination. The AoI measures the time that elapsed since the generation of the packet that was most recently delivered to the destination. In this paper, we consider a single-hop wireless network with a number of nodes transmitting time-sensitive information to a Base Station and address the problem of minimizing the Expected Weighted Sum AoI of the network while simultaneously satisfying timely-throughput constraints from the nodes. We develop three low-complexity transmission scheduling policies that attempt to minimize AoI subject to minimum throughput requirements and evaluate their performance against the optimal policy. In particular, we develop a randomized policy, a Max-Weight policy and a Whittle's Index policy, and show that they are guaranteed to be within a factor of two, four and eight, respectively, away from the minimum AoI possible. In contrast, simulation results show that Max-Weight outperforms the other policies, both in terms of AoI and throughput, in every network configuration simulated, and achieves near optimal performance.

258 citations

Journal ArticleDOI
TL;DR: A single-hop wireless network with a number of nodes transmitting time-sensitive information to a base station is considered and the problem of minimizing the expected weighted sum AoI of the network while simultaneously satisfying timely-throughput constraints from the nodes is addressed.
Abstract: Age of Information (AoI) is a performance metric that captures the freshness of the information from the perspective of the destination. The AoI measures the time that elapsed since the generation of the packet that was most recently delivered to the destination. In this paper, we consider a single-hop wireless network with a number of nodes transmitting time-sensitive information to a base station and address the problem of minimizing the expected weighted sum AoI of the network while simultaneously satisfying timely-throughput constraints from the nodes. We develop four low-complexity transmission scheduling policies that attempt to minimize AoI subject to minimum throughput requirements and evaluate their performance against the optimal policy. In particular, we develop a randomized policy, a Max-Weight policy, a Drift-Plus-Penalty policy, and a Whittle’s Index policy, and show that they are guaranteed to be within a factor of two, four, two, and eight, respectively, away from the minimum AoI possible. The simulation results show that Max-Weight and Drift-Plus-Penalty outperform the other policies, both in terms of AoI and throughput, in every network configuration simulated, and achieve near-optimal performance.

186 citations

Journal ArticleDOI
TL;DR: The Universal Max-Weight (UMW) as discussed by the authors policy is the first known throughput-optimal policy of such versatility in the context of generalized network flow problems, which is derived by relaxing the precedence constraints associated with multi-hop routing and then solving a min-cost routing and max-weight scheduling problem on a virtual network of queues.
Abstract: We consider the problem of throughput-optimal packet dissemination, in the presence of an arbitrary mix of unicast, broadcast, multicast, and anycast traffic, in an arbitrary wireless network. We propose an online dynamic policy, called Universal Max-Weight (UMW), which solves the problem efficiently. To the best of our knowledge, UMW is the first known throughput-optimal policy of such versatility in the context of generalized network flow problems. Conceptually, the UMW policy is derived by relaxing the precedence constraints associated with multi-hop routing and then solving a min-cost routing and max-weight scheduling problem on a virtual network of queues . When specialized to the unicast setting, the UMW policy yields a throughput-optimal cycle-free routing and link scheduling policy. This is in contrast with the well-known throughput-optimal back-pressure (BP) policy which allows for packet cycling, resulting in excessive latency. Extensive simulation results show that the proposed UMW policy incurs a substantially smaller delay as compared with the BP policy. The proof of throughput-optimality of the UMW policy combines ideas from the stochastic Lyapunov theory with a sample path argument from adversarial queueing theory and may be of independent theoretical interest.

28 citations

Proceedings ArticleDOI
05 Jul 2016
TL;DR: In this paper, a new online throughput-optimal broadcast algorithm is proposed, which takes packet-by-packet scheduling and routing decisions, obviating the need for maintaining any global topological structures, such as spanning-trees.
Abstract: We consider the problem of throughput-optimal broadcasting in time-varying wireless network with an underlying Directed Acyclic Graph (DAG) topology. Known broadcast algorithms route packets along pre-computed spanning trees. In large wireless networks with time-varying connectivities, the optimal trees are difficult to compute and maintain. In this paper we propose a new online throughput-optimal broadcast algorithm, which takes packet-by-packet scheduling and routing decisions, obviating the need for maintaining any global topological structures, such as spanning-trees. Our algorithm utilizes certain queue-like system-state information for making transmission decisions and hence, may be thought of as a generalization of the well-known back pressure algorithm, which makes point-to-point unicast transmission decisions based on local queue-length information. Technically, the back-pressure algorithm is derived by stabilizing the packet-queues. However, because of packet-duplications, the work-conservation principle is violated and appropriate queuing processes are difficult to define in the broadcast setting. To address this fundamental issue, we identify certain state-variables whose dynamics behave like virtual queues. By stochastically stabilizing these virtual queues, we devise a throughput-optimal broadcast policy. We also derive new characterizations of the broadcast-capacity of time-varying wireless DAGs and derive an efficient algorithm to compute the capacity exactly under certain assumptions, and a poly-time approximation algorithm for computing the capacity approximately under less restrictive assumptions.

23 citations


Cited by
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Journal ArticleDOI
TL;DR: Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols used xiii 1.
Abstract: Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols Used xiii 1. The Importance of Islands 3 2. Area and Number of Speicies 8 3. Further Explanations of the Area-Diversity Pattern 19 4. The Strategy of Colonization 68 5. Invasibility and the Variable Niche 94 6. Stepping Stones and Biotic Exchange 123 7. Evolutionary Changes Following Colonization 145 8. Prospect 181 Glossary 185 References 193 Index 201

14,171 citations

Journal ArticleDOI
TL;DR: Several important aspects of in-band FDR are identified: basics, enabling technologies, information-theoretical performance analysis, key design issues and challenges, and some broader perspectives for in- band FDR.
Abstract: Recent advances in self-interference cancellation techniques enable in-band full-duplex wireless systems, which transmit and receive simultaneously in the same frequency band with high spectrum efficiency. As a typical application of in-band full-duplex wireless, in-band full-duplex relaying (FDR) is a promising technology to integrate the merits of in-band full-duplex wireless and relaying technology. However, several significant research challenges remain to be addressed before its widespread deployment, including small-size full-duplex device design, channel modeling and estimation, cross-layer/joint resource management, interference management, security, etc. In this paper, we provide a brief survey on some of the works that have already been done for in-band FDR, and discuss the related research issues and challenges. We identify several important aspects of in-band FDR: basics, enabling technologies, information-theoretical performance analysis, key design issues and challenges. Finally, we also explore some broader perspectives for in-band FDR.

480 citations

Journal ArticleDOI
TL;DR: A new book enPDFd comparison methods for queues and other stochastic models that can be a new way to explore the knowledge and one thing to always remember in every reading time, even step by step is shown.
Abstract: Studies stochastic models of queueing, reliability, inventory, and sequencing in which random influences are considered. One stochastic mode--rl is approximated by another that is simpler in structure or about which simpler assumptions can be made. After general results on comparison properties of random variables and stochastic processes are given, the properties are illustrated by application to various queueing models and questions in experimental design, renewal and reliability theory, PERT networks and branching processes.

472 citations

Book
01 Jan 2016
TL;DR: It’s time to dust off the gloves and get ready for the cold weather.
Abstract: 1 インフラを構築する(AWSにおけるインフラ;VPCを構成する;VPCとオンプレミス環境とを接続する) 2 ファイルオブジェクトを保存・共有・公開する(オブジェクトストレージS3の機能;ファイルストレージとして利用する;Webサーバーを構築する;信頼性とコストのバランスをとりたい) 3 アプリケーションサーバーを構築する(Amazon EC2とAWS Lambda;スケーラビリティーを高める;サーバーレスでプログラムを動かす;データベースサービスを活用する) 4 AWSシステムを管理する(リソース監視と異常検知・通報;耐障害性を高める仕組みとバックアップ&リカバリー;構成管理)

350 citations

Posted Content
TL;DR: The current state of the art in the design and optimization of low-latency cyberphysical systems and applications in which sources send time-stamped status updates to interested recipients is described and AoI timeliness metrics are described.
Abstract: We summarize recent contributions in the broad area of age of information (AoI). In particular, we describe the current state of the art in the design and optimization of low-latency cyberphysical systems and applications in which sources send time-stamped status updates to interested recipients. These applications desire status updates at the recipients to be as timely as possible; however, this is typically constrained by limited system resources. We describe AoI timeliness metrics and present general methods of AoI evaluation analysis that are applicable to a wide variety of sources and systems. Starting from elementary single-server queues, we apply these AoI methods to a range of increasingly complex systems, including energy harvesting sensors transmitting over noisy channels, parallel server systems, queueing networks, and various single-hop and multi-hop wireless networks. We also explore how update age is related to MMSE methods of sampling, estimation and control of stochastic processes. The paper concludes with a review of efforts to employ age optimization in cyberphysical applications.

265 citations