A transmission scheme for robust delivery of urgent/critical data in Internet of Things

Sharma, Hrishikesh; Balamuralidhar, P.

doi:10.1109/comsnets.2013.6465552

Cited by 4 publications

(2 citation statements)

References 17 publications

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“…In [13], a compressive sensing based approach is proposed to recover sparse signals from multiple spatially correlated data transmitted to a fusion center. Recently in [14], researchers have proposed techniques to reduce the amount of packets to be retransmitted in case of faulty transmission eventually saving energy.…”

Section: B Channel Statistics For Wireless Energy Harvesting Iot Sysmentioning

confidence: 99%

Wireless energy harvesting for the Internet of Things

et al. 2015

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Internet of Things (IoT) is an emerging computing concept that describes a structure in which everyday physical objects, each provided with unique identifiers, are connected to the Internet without requiring human interaction.Long-term and self-sustainable operation are key components for realization of such a complex network, and entail energy-aware devices that are potentially capable of harvesting their required energy from ambient sources. Among different energy harvesting methods such as vibration, light and thermal energy extraction, wireless energy harvesting (WEH) has proven to be one of the most promising solutions by virtue of its simplicity, ease of implementation and availability. In this article, we present an overview of enabling technologies for efficient WEH, analyze the life-time of WEH-enabled IoT devices, and briefly study the future trends in the design of efficient WEH systems and research challenges that lie ahead.

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Section: B Channel Statistics For Wireless Energy Harvesting Iot Sysmentioning

confidence: 99%

Wireless energy harvesting for the Internet of Things

et al. 2015

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“…Specially, the specialized delivery scheme in the context of IOT, was proposed by H. Sharma et al [19] based on usage of byte-level error-correction codes, which is used to improve relevant delivery parameters. In article [20], the author considered error correction codes with simple block code, which is used to improve the transmission performance of molecular communications.…”

Section: Related Workmentioning

confidence: 99%

Reliable Transmission Control Scheme Based on FEC Sensing and Adaptive MIMO for Mobile Internet of Things

Li¹,

Feng²,

Jin³

et al. 2014

JCM

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In mobile Internet of Things, it is one key issue how to provide the reliable guarantee of transmission over sensors in connection with the services diversity, dynamic topology and various unknown interference. To solve these problems, we analyzed the Forward Error Control (FEC) sensing technology based on Cyclic Redundancy Check (CRC) and adaptive Multiple Input Multiple Output (MIMO) approach, building upon which we proposed the reliable transmission control scheme, in order to guarantee the Quality of Services. The mathematical analyses and NS simulation results show that the proposed transmission control scheme maintain the better performance such as throughput, reliability, real time performance and energy efficiency, than the FEC alone and MIMO alone approaches. Index Terms-Mobile internet of tings, FEC sensing, adaptive multiple-input multiple-output, reliable transmission I. INTRODUCTION Perception of the physical world and process of change, a lot of objects should be detected [1], [2], including temperature, pressure, humidity, strain, so the miniaturization and low-power sensors for applications is important and significant. There are some challenging issues of design, communication and transmission over sensors in Mobile Internet of Things (MIOT). Wireless communication environment of MIOT is dynamic and harsh, which have various interferences. Transmission and communication over this channel is susceptible to such distortions as finite bandwidth, resources, mobility, application service diversity, etc [3], [4]. These restrictions, combined with the characteristics of sensor networks [5] such as limited computation ability, storage and self-organization, make it difficult to guarantee Quality of Services (QoS) over MIOT.

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