Energy Efficient Communication And Rate Control Algorithms For Wireless Sensor Networks
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Energy Efficient Communication and Rate Control Algorithms for Wireless Sensor Networks
Sensor networks provide applications in many diverse areas. This is for the simple fact that they are reliable, flexible, easily deployable and highly cost-effective. Smart sensors can provide such diverse services as detecting signs of machine failures, sensing earthquakes, onset of flooding and even provide a warning system for potential terrorist attacks. Because the sensors are untethered and battery powered, these networks have to maintain a high yield to the energy spent per sensor device. These yields translate into mainly throughputs and packet latencies while keeping the energy usage at the minimum. In this work, we look at the communication level energy usage within the sensor networks and propose novel scheme for channel access optimized for energy consumption and rate control algorithms for traffic engineering and congestion control in wireless sensor networks. The first involves a novel medium access protocol for wireless sensor networks. The protocol is based on exploiting the periodicity inherent in carrier sensing schemes like CSMA/CA combined with a relaxed time-access arbitration regime among the competing nodes. Transmission and reception of data frames are made to be strictly receiver triggered events which makes it possible to bring down idle-listening drastically. The protocol also provides a way to make the channel access collision-free among the two-degree neighbors. PMAC requires no additional control signaling and no network-wide synchronization. The protocol does not seek to make any tradeoff for the gains in energy efficiency with latency or throughput. It presents high-energy efficiency and throughput improvement in low as well as high-traffic scenarios of sleeping. In the second part, we propose novel rate-control algorithms for the wireless sensor networks. There has been a growth in personal area network technologies like Bluetooth etc to support various applications that require multimedia level QoS in a high interference environment. Applications such as voice data traffic, file transfers, periodic synching of electronic devices within the range of 10m-15m requires sophisticated yet simple channel access techniques that accommodate different QoS requirements of these applications. In this context, the new rate control algorithms were designed that reduces the interference and maximized the throughput and reliability parameters such as packet success rates, packet latency and aggregate throughput per flow. Moreover, the rate control algorithm also takes into account the fairness issues among the competing flows in terms of the bandwidth-share.
Handbook of Algorithms for Wireless Networking and Mobile Computing
The Handbook of Algorithms for Wireless Networking and Mobile Computing focuses on several aspects of mobile computing, particularly algorithmic methods and distributed computing with mobile communications capability. It provides the topics that are crucial for building the foundation for the design and construction of future generations of mobile and wireless networks, including cellular, wireless ad hoc, sensor, and ubiquitous networks. Following an analysis of fundamental algorithms and protocols, the book offers a basic overview of wireless technologies and networks. Other topics include issues related to mobility, aspects of QoS provisioning in wireless networks, future applications, and much more.
2nd EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing
Author: Anandakumar Haldorai
language: en
Publisher: Springer Nature
Release Date: 2020-09-30
This proceeding features papers discussing big data innovation for sustainable cognitive computing. The papers feature details on cognitive computing and its self-learning systems that use data mining, pattern recognition and natural language processing (NLP) to mirror the way the human brain works. This international conference focuses on cognitive computing technologies, from knowledge representation techniques and natural language processing algorithms to dynamic learning approaches. Topics covered include Data Science for Cognitive Analysis, Real-Time Ubiquitous Data Science, Platform for Privacy Preserving Data Science, and Internet-Based Cognitive Platform. The 2nd EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing (BDCC 2019) took place in Coimbatore, India on December 12-13, 2019. Contains proceedings from 2nd EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing (BDCC 2019), Coimbatore, India, December 12-13, 2019; Features topics ranging from Data Science for Cognitive Analysis to Internet-Based Cognitive Platforms; Includes contributions from researchers, academics, and professionals from around the world.