Energy Efficient Computation And Communication Scheduling For Cluster Based In Network Processing In Large Scale Wireless Sensor Networks
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Energy-efficient Computation and Communication Scheduling for Cluster-based In-network Processing in Large-scale Wireless Sensor Networks
Abstract: Emerging Wireless Sensor Networks (WSN) applications demand considerable computation capacity for in-network processing. To achieve the required processing capacity, cross-layer collaborative in-network processing among sensors emerges as a promising solution: Sensors not only process information at the application layer, but also synchronize their communication activities to exchange partially processed data for parallel processing. Task mapping and scheduling plays an important role in parallel processing. Though this problem has been extensively studied in the high performance computing area, its counterpart in WSNs remains largely unexplored. Scheduling computation and communication events is a challenging problem in WSNs due to limited resource availability and shared communication medium. This research investigates the energy-efficient task mapping and scheduling problem in large-scale WSNs composed of homogeneous wireless sensors. A hierarchical WSN architecture is assumed to be composed of sensor clusters, where applications are iteratively executed. Given this environment, task mapping and scheduling in single-hop clustered WSNs is investigated for energy-constrained applications. Based on the proposed Hyper-DAG model and single-hop channel model, the EcoMapS solution minimizes schedule lengths subject to energy consumption constraints. Secondly, real-time applications are also considered in single-hop clustered WSNs. Incorporating the novel Dynamic Voltage Scaling (DVS) algorithm, the RT-MapS solution provides deadline guarantee with the minimum balanced energy consumption. Next, the task mapping and scheduling problem is further addressed in its general form for multi-hop clustered WSNs. A novel multi-hop channel model is developed, and a multi-hop communication scheduling algorithm is presented, based on which the MTMS solution minimizes application energy consumption subject to deadline constraints. Finally, low-complexity sensor failure handling algorithms are developed to recover network functionality when sensors failures occur in single-hop and multi-hop clustered WSNs.
Energy-Efficient Computing and Communication
Information and communication technology (ICT) is reponsible for up to 10% of world power consumption. In particular, communications and computing systems are indispensable elements in ICT; thus, determining how to improve the energy efficiency in communications and computing systems has become one of the most important issues for realizing green ICT. Even though a number of studies have been conducted, most of them focused on one aspect—either communications or computing systems. However, salient features in communications and computing systems should be jointly considered, and novel holistic approaches across communications and computing systems are strongly required to implement energy-efficient systems. In addition, emerging systems, such as energy-harvesting IoT devices, cyber-physical systems (CPSs), autonomous vehicles (AVs), and unmanned aerial vehicles (UAVs), require new approaches to satisfy their strict energy consumption requirements in mission-critical situations. The goal of this Special Issue is to disseminate the recent advances in energy-efficient communications and computing systems. Review and survey papers on these topics are welcome. Potential topics include, but are not limited to, the following: • energy-efficient communications: from physical layer to application layer; • energy-efficient computing systems; • energy-efficient network architecture: through SDN/NFV/network slicing; • energy-efficient system design; • energy-efficient Internet of Things (IoT) and Industrial IoT (IIoT); • energy-efficient edge/fog/cloud computing; • new approaches for energy-efficient computing and communications (e.g., AI/ML and data-driven approaches); • new performance metrics on energy efficiency in emerging systems; • energy harvesting and simultaneous wireless information and power transfer (SWIPT); • smart grid and vehicle-to-grid (V2G); and • standardization and open source activities for energy efficient systems.
Large Scale Network-Centric Distributed Systems
Author: Hamid Sarbazi-Azad
language: en
Publisher: John Wiley & Sons
Release Date: 2013-10-10
A highly accessible reference offering a broad range of topics and insights on large scale network-centric distributed systems Evolving from the fields of high-performance computing and networking, large scale network-centric distributed systems continues to grow as one of the most important topics in computing and communication and many interdisciplinary areas. Dealing with both wired and wireless networks, this book focuses on the design and performance issues of such systems. Large Scale Network-Centric Distributed Systems provides in-depth coverage ranging from ground-level hardware issues (such as buffer organization, router delay, and flow control) to the high-level issues immediately concerning application or system users (including parallel programming, middleware, and OS support for such computing systems). Arranged in five parts, it explains and analyzes complex topics to an unprecedented degree: Part 1: Multicore and Many-Core (Mc) Systems-on-Chip Part 2: Pervasive/Ubiquitous Computing and Peer-to-Peer Systems Part 3: Wireless/Mobile Networks Part 4: Grid and Cloud Computing Part 5: Other Topics Related to Network-Centric Computing and Its Applications Large Scale Network-Centric Distributed Systems is an incredibly useful resource for practitioners, postgraduate students, postdocs, and researchers.