Optimal stopping for energy efficiency with delay constraints in Cognitive Radio networks

Zhao, Bin; Friderikos, Vasilis

doi:10.1109/pimrc.2012.6362897

Cited by 14 publications

(34 citation statements)

References 16 publications

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“…This study models the energy consumed by the store and carry process (Esc) following the indications reported in [8]. The storage energy consumption is estimated considering that mobile devices store the received data packets in a This study focuses on a 2-hop uplink MCN scenario where a static SN wants to upload a message of size F to a BS before a deadline T (Fig.…”

Section: ) Energy Consumptionmentioning

confidence: 99%

“…storage unit (DRAM), and that the received information is (1) transferred to an internal NAND flash unit to reduce the storage energy consumption [8].…”

Section: ) Energy Consumptionmentioning

confidence: 99%

“…The file that SN needs to upload to the BS has a nominal size of F=10Mb, and it has to be transmitted to the BS before the deadline T=60s. The energy consumed at mobile devices due to the � tore and carr y process has been obtained from [8]. The 'AREA-PRBs' scheme is evaluated with the probability 6 eq � al to 0.9 and !…”

Section: P Erformance Ev Aluatlonmentioning

confidence: 99%

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Energy benefits of opportunistic device-centric wireless networks

Coll-Perales

Gozálvez

2015

2015 15th International Conference on Intelligent Systems Design and Applications (ISDA)

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Device-centric wireless networks, and in particular Multi-hop Cellular Networks (MCN), can improve the capacity and efficiency of wireless networks, and will hence represent a significant element of the 5G ecosystem. Additional gains can be achieved for mobile delay tolerant services when integrating opportunistic networking in device-centric wireless networks. This paper proposes a solution for such integration that is evaluated for the case of 2-hop uplink opportunistic MCN communications. The proposed solution takes into to account the fact that mobile relays might not always be available at the optimum location and time instant, and the fact that sufficient cellular radio resources might not be available when mobile relays want to start forwarding the information towards the base station. The conducted study shows that the proposed scheme can reduce the energy consumption by more than 80% compared to traditional single-hop cellular communications.

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Section: ) Energy Consumptionmentioning

confidence: 99%

“…storage unit (DRAM), and that the received information is (1) transferred to an internal NAND flash unit to reduce the storage energy consumption [8].…”

Section: ) Energy Consumptionmentioning

confidence: 99%

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Energy benefits of opportunistic device-centric wireless networks

Coll-Perales

Gozálvez

2015

2015 15th International Conference on Intelligent Systems Design and Applications (ISDA)

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“…The energy consumption regarding SU wireless message transmission can be formulated as in [31], shown in the equation below where d e represent the energy consumption of the op-amp and B represents the data transmission rate. Within cognitive radio (CR) networks, the SU transmission is trying to explore white space of wireless spectrum while at the same time avoiding interfering with the PU traffic.…”

Section: Network Protocols and Algorithmsmentioning

confidence: 99%

Increased Energy Efficiency via Delay-Tolerant Transmissions in Cognitive Radio Networks

Zhao

Friderikos

2013

NPA

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We are currently witnessing the emergence of two important trends in wireless networks, namely the increased usage of Internet like applications, many of them which are delay tolerant, and cognitive radio techniques. In this paper, the focus is on how to capitalize the delay tolerance of various applications (such as email, Peer to Peer networks, social networking & operating system updates and file transfers to mention just a few) to reduce the energy consumption in cognitive networks. Since it becomes feasible to estimate the Primary Users (PU) connections for the Secondary Users (SU) by contacting a trusted database containing the information of PU traffic, a scheme is proposed that explicitly utilize the distribution of SU traffic loads to provide load-balancing. By modeling the problem under investigation as an M/M/K/L queuing system, the performance of the SUs competition is analyzed under various traffic blocking thresholds and queuing delays. To this end, by optimizing the frequency channel utilization, the number of SU connection that can be accommodated simultaneously is derived. A wide set of numerical investigations reveal how message transmission delays and the use of available white spaces can reduce the energy consumption without affecting PU traffic.

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“…When Adaptive Modulation and Coding (AMC) is capable in cellular networks [10], the cell can be separated into n concentric rings of radii R i , i = 1, · · · , N according to the distance between the wireless device and its serving BS. The set of available modulation and coding schemes is denoted by…”

Section: A Cellular Networkmentioning

confidence: 99%

Extending recharging cycles of mobile devices with intelligent use of wireless interfaces

Zhao

Friderikos

2013

2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)

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The increased usage of smartphones and the rich ecosystem of Internet applications are having a severe effect on the recharging cycles of devices due to the increased levels of energy consumption and limitations of battery technology. As the infrastructure of hotspots for Wi-Fi and TVWS (TV White Space) interfaces have become ubiquitously available in urban areas, the energy usage in modern devices for transmitting a fixed amount of data could differ drastically due to the significant difference on the achievable data rates on these radios. As a result, techniques that can reduce the energy cost for Internet applications with emphasis on the client side would effectively increase the battery lifetime of digital devices. To this end, we introduce a strategy that deploy roadside infrastructure Wi-Fi Access Points (AP) and determine available spectrum (TVWS) at a given location to assist the data delivery for mobile devices according to corresponding on-line service features of mobile applications. In this framework, we incorporate a probabilistic analysis for spectrum availability and cell residence time of vehicle mobility. Numerical investigations reveal that the proposed set of schemes could increase the battery lifespans by up to 25%.

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Optimal stopping for energy efficiency with delay constraints in Cognitive Radio networks

Cited by 14 publications

References 16 publications

Energy benefits of opportunistic device-centric wireless networks

Energy benefits of opportunistic device-centric wireless networks

Increased Energy Efficiency via Delay-Tolerant Transmissions in Cognitive Radio Networks

Extending recharging cycles of mobile devices with intelligent use of wireless interfaces

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