Cross-Layer Energy and Delay Optimization in Small-Scale Sensor Networks

Cui, Shuguang; Madan, Ritesh; Goldsmith, Andrea; Lall, Sanjay

doi:10.1109/twc.2007.060072

Cited by 110 publications

(75 citation statements)

References 16 publications

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“…[59], [60]. A number of metrics have been proposed for EE networks/systems to efficiently evaluate the effect of novel techniques towards achieving green communications systems.…”

Section: ) Equipment Level Metricsmentioning

confidence: 99%

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Energy Efficiency Tradeoff Mechanism Towards Wireless Green Communication: A Survey

Mahapatra¹,

Nijsure

Kaddoum

et al. 2016

IEEE Commun. Surv. Tutorials

177

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Abstract-Energy efficient (EE) communication has earnedtremendous interest in recent years due to ever increasing number of wireless devices operating in shrinking cells, while demanding high data rates with high Quality of Services (QoS) and Quality of Expectation (QoE). To support these objectives, energy is consumed in every protocol layer. Establishing and maintaining a successful wireless communication link to simultaneously achieve all these objectives becomes challenging since the energy consumption requirements of the user and network are different for different objectives. Thus, there is a need for tradeoff techniques to achieve energy efficiency in each protocol layer. In this paper, we provide a survey of different tradeoff mechanisms proposed in the literature. The EE tradeoffs have been classified based on each protocol layer and discussed its affect in the network energy efficiency. These other QoS parameters include spectral efficiency, deployment, delay, routing, scheduling, bandwidth and coding etc. This survey also discusses the various EE techniques to improve energy-efficiency in infrastructure mode. Finally, the work provides an discussion, where impact of EE tradeoffs have been presented based on different wireless architecture towards realizing a green wireless communication network.

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“…[59], [60]. A number of metrics have been proposed for EE networks/systems to efficiently evaluate the effect of novel techniques towards achieving green communications systems.…”

Section: ) Equipment Level Metricsmentioning

confidence: 99%

“…These techniques improve the SE of the system and availability of these techniques is also directly related to SE and EE [64]. This improvement is limited by delay in different protocol layer, such as delay due to scheduling, routing and transport [59], [62], [65]- [70].…”

Section: Tradeoff Mechanisms Overviewmentioning

confidence: 99%

Energy Efficiency Tradeoff Mechanism Towards Wireless Green Communication: A Survey

Mahapatra¹,

Nijsure

Kaddoum

et al. 2016

IEEE Commun. Surv. Tutorials

177

View full text Add to dashboard Cite

show abstract

“…Small scale networks where sensor nodes are closely located are studied in [7]. TDMA is assumed as an access method.…”

Section: Related Workmentioning

confidence: 99%

Multihop Routing for Energy Efficiency in Wireless Sensor Networks

Yaacoub¹,

Abu-Dayya²

2012

Wireless Sensor Networks - Technology and Protocols

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“…In addition to those separate-layer solutions mentioned above, there are some research work using cross-layer schemes for delay optimization. Cui et al [9] considered joint design of network layer, MAC layer and physical layer for delay optimization. They optimized the routing flow, TDMA slot assignment and MQAM modulation rate and power on each link to minimize worst-case packet delay.…”

Section: Related Workmentioning

confidence: 99%

Minimum Delay Routing in Multihop Wireless Networks

Cheng

Gong

Wan

2011

Wireless Algorithms, Systems, and Applications

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Abstract. End-to-end delay is an important QoS metric in multihop wireless networks such as sensor networks and mesh networks. Along with throughput, end-to-end delay determines the user-experienced data transmission time. End-to-end delay refers to the total time it takes for a single packet to reach the destination. It is a result of many factors including the length of the route and the interference level along the route, and therefore both the routing scheme and the MAC layer scheduling scheme can affect end-to-end delay. We assume a deterministic scheduling scheme is used at the MAC layer. Since the actual delay depends on the MAC layer scheduling algorithm, at the network layer we try to reduce the interference on the path instead of the actual delay time. To find the routing solution that minimizes path interference, a sufficient condition on conflict-free transmission is established, which helps to quantify the interference on a link. A linear program based on the sufficient condition is developed to compute the routing solution. Through simulation, we show that the proposed routing scheme can effectively reduce end-to-end delay.

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Cross-Layer Energy and Delay Optimization in Small-Scale Sensor Networks

Cited by 110 publications

References 16 publications

Energy Efficiency Tradeoff Mechanism Towards Wireless Green Communication: A Survey

Energy Efficiency Tradeoff Mechanism Towards Wireless Green Communication: A Survey

Multihop Routing for Energy Efficiency in Wireless Sensor Networks

Minimum Delay Routing in Multihop Wireless Networks

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