Joint Optimization of Radio and Virtual Machine Resources With Uncertain User Demands in Mobile Cloud Computing

Li, Yun; Liu, Jie; Wang, Chonggang

doi:10.1109/tmm.2018.2796246

Cited by 109 publications

(39 citation statements)

References 26 publications

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“…The proposed MC system is illustrated in Figure 1. The proposed communication system is motivated by the experience of multiple traditional communication systems [18,19,20,21,22,23]. Specifically, the communication system is modeled as a chain, which is composed of a sender, a receiver and three types of communication media.…”

Section: Overview Of the Communication Systemmentioning

confidence: 99%

Chain Modeling of Molecular Communications for Body Area Network

Han

Liu

2019

Sensors

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Molecular communications provide an attractive opportunity to precisely regulate biological signaling in nano-medicine applications of body area networks. In this paper, we utilize molecular communication tools to interpret how neural signals are generated in response to external stimuli. First, we propose a chain model of molecular communication system by considering three types of biological signaling through different communication media. Second, communication models of hormonal signaling, Ca2+ signaling and neural signaling are developed based on existing knowledge. Third, an amplify-and-forward relaying mechanism is proposed to connect different types of signaling. Simulation results demonstrate that the proposed communication system facilitates the information exchange between the neural system and nano-machines, and suggests that proper adjustment can optimize the communication system performance.

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Section: Overview Of the Communication Systemmentioning

confidence: 99%

Chain Modeling of Molecular Communications for Body Area Network

Han

Liu

2019

Sensors

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“…If a node has multiple incoming links, it can receive multiple individual packets by deploying, for example, multipacket reception techniques [55,56]. Even though a node can receive multiple packets at a single 6 This connection boundary in terms of the Euclidean distance is motivated by realistic communication problems such as limited power budget of a node and interference among wireless nodes. 7 Note that this assumption can be easily generalized to Ω bits per unit slot for a constant Ω. time slot, under the conventional SF relaying architecture, a node cannot transmit more than one packet at a time because of the link capacity constraints.…”

Section: Network Model and Inter-link Dependency Conditionmentioning

confidence: 99%

Distributed topology design for network coding deployed networks

Kwon

Park

2019

Signal Processing

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“…e performance gain is significant because of the combination of encoding, interleaving, and iterative decoding. Especially in future IoT, much computing resource will move towards the edge network to supplement the traditional remote cloud center [17][18][19]. Increasing computational power in the sink node continues to open the door to more sophisticated algorithms.…”

Section: Introductionmentioning

confidence: 99%

A New Multiple-Symbol Differential Detection Strategy for Error-Floor Elimination of IEEE 802.15.4 BPSK Receivers Impaired by Carrier Frequency Offset

Zhang

Han

et al. 2019

Wireless Communications and Mobile Computing

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In this paper, we pay our attention towards the noncoherent demodulation aspect of binary phase shift keying (BPSK) receivers for IEEE 802.15.4 wireless sensor networks (WSNs), and a carrier frequency offset invariant as well as error-floor free multiple-symbol differential detection (MSDD) strategy is proposed over the flat fading channel. This detector is an alternative to the multiple-symbol detector that has been considered almost exclusively in the past. In this new configuration, the receivers do not perform chip-level precompensation as in conventional scheme but bit-level postcompensation. That is, the bit-level autocorrelation operation is first implemented with the “raw” chip sample, and then the carrier frequency offset effect (CFOE) embedded in the achieved statistic is compensated. Correspondingly, the cumulative error in the detection metric is decreased so much that the pervasive error floor for the conventional MSDD scheme is suppressed. Also, complexity efficient estimators for the MSDD scheme are reinvestigated, analyzed, and summarized. Simulation results demonstrate that this new detection strategy may achieve rather more encouraging gain from differential and spread spectrum coding than the conventional single differential coherent detection (SDCD) scheme. The pervasive error floor is also eliminated as compared with conventional MSDD scheme even if the most simple estimator is configured under large bit observation length. Then, much transmitting energy may be saved for each chip symbol, which is practically desired for transmit-only nodes in WSNs.

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Joint Optimization of Radio and Virtual Machine Resources With Uncertain User Demands in Mobile Cloud Computing

Cited by 109 publications

References 26 publications

Chain Modeling of Molecular Communications for Body Area Network

Chain Modeling of Molecular Communications for Body Area Network

Distributed topology design for network coding deployed networks

A New Multiple-Symbol Differential Detection Strategy for Error-Floor Elimination of IEEE 802.15.4 BPSK Receivers Impaired by Carrier Frequency Offset

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