VECMAN: A Framework for Energy-Aware Resource Management in Vehicular Edge Computing Systems

Bahreini, Tayebeh; Brocanelli, Marco; Grosu, Daniel

doi:10.1109/tmc.2021.3089338

Cited by 18 publications

(17 citation statements)

References 24 publications

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“…The parallel execution of these applications can be obtained using multi processing approaches [79]. In the context of Fog computing, several works such as [13,20,84,89] have considered monolithic applications.…”

Section: Architectural Designmentioning

confidence: 99%

“…These properties can significantly affect the scheduling decision to find proper FSs or CSs for an application. The CCR defines whether an application on average is more 1) computation-intensive [42,101,132] or 2) communication-intensive [13,49,116]. Besides, some works consider a range of applications to cover both computationintensive and communication-intensive applications, to which we refer as 3) hybrid [16,40].…”

Section: Communication-computation Ratio (Ccr)mentioning

confidence: 99%

“…The main perspective of several proposals is to satisfy the requirements of IoT applications such as minimizing their execution time and energy consumption of IoT devices, or improving user experience in terms of QoS and Quality of Experinece (QoE). Several works have considered IoT perspective for the optimization such as [13,73,114,114,124,134].…”

Section: Main Perspectivementioning

confidence: 99%

“…Moreover, nearly 40% of surveyed works assume a two-tier model for the organization of end-users and resources. These works mostly assume real-time workload type and communication-intensive applications for the deployment on Edge servers, such as [13,22,53,110].…”

mentioning

confidence: 99%

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Scheduling IoT Applications in Edge and Fog Computing Environments: A Taxonomy and Future Directions

Goudarzi¹,

Palaniswami²,

Buyya³

2022

Preprint

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Fog computing, as a distributed paradigm, offers cloud-like services at the edge of the network with low latency and high-access bandwidth to support a diverse range of IoT application scenarios. To fully utilize the potential of this computing paradigm, scalable, adaptive, and accurate scheduling mechanisms and algorithms are required to efficiently capture the dynamics and requirements of users, IoT applications, environmental properties, and optimization targets. This paper presents a taxonomy of recent literature on scheduling IoT applications in Fog computing. Based on our new classification schemes, current works in the literature are analyzed, research gaps of each category are identified, and respective future directions are described. CCS Concepts: • General and reference → General literature; • Computer systems organization → Distributed architectures.

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Section: Architectural Designmentioning

confidence: 99%

Section: Communication-computation Ratio (Ccr)mentioning

confidence: 99%

Section: Main Perspectivementioning

confidence: 99%

mentioning

confidence: 99%

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Scheduling IoT Applications in Edge and Fog Computing Environments: A Taxonomy and Future Directions

Goudarzi¹,

Palaniswami²,

Buyya³

2022

Preprint

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“…Therefore, energy can be saved by coordinating vehicles under different work modes for completing the offloaded task. T. Bahreini et al [115] propose an energy-aware resource management framework in vehicular edge computing systems, where energy-efficiency can be improved through sharing and coordinating computing resources among connected EVs. To determine the participating vehicles and resource sharing duration with the unpredictable future locations of vehicles, they design a resource selection algorithm and an energy manager algorithm to select the vehicle state (i.e., requester or provider), the number of workload replications, and the amount of offloaded workload so as to minimize the computation energy consumption of all participating vehicles.…”

Section: Mec With Vehicular Serversmentioning

confidence: 99%

Green Internet of Vehicles (IoV) in the 6G Era: Toward Sustainable Vehicular Communications and Networking

Wang¹,

Zhu²,

Hossain³

2021

Preprint

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As one of the most promising applications in future Internet of Things, Internet of Vehicles (IoV) has been acknowledged as a fundamental technology for developing the Intelligent Transportation Systems in smart cities. With the emergence of the sixth generation (6G) communications technologies, massive network infrastructures will be densely deployed and the number of network nodes will increase exponentially, leading to extremely high energy consumption. There has been an upsurge of interest to develop the green IoV towards sustainable vehicular communication and networking in the 6G era. However, as a special mobile ad-hoc network, the energy cost in an IoV system involves the communication and computation energy in addition to the fuel consumption and the electricity cost of moving vehicles. Moreover, the energy harvesting technology, which is likely to be adopted widely in 6G systems, will complicate the optimization of energy efficiency in the entire system. Current studies focus only on part of the energy issues in IoV systems without a comprehensive discussion of the state-of-the-art energy-efficient approaches and the influence of the development of 6G networks on green IoV. In this paper, we present the main considerations for green IoV from five different scenarios, including the communication, computation, traffic, Electric Vehicles (EVs), and energy harvesting management. The literatures relevant to each of the scenarios are compared from the perspective of energy optimization (e.g., with respect to resource allocation, workload scheduling, routing design, traffic control, charging management, energy harvesting and sharing, etc.) and the related factors affecting energy efficiency (e.g., resource limitation, channel state, network topology, traffic condition, etc.). In addition, we introduce the potential challenges and the emerging technologies in 6G for developing green IoV systems. Finally, we discuss the research trends in designing energy-efficient IoV systems.

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Towards High-Quality Battery Life for Autonomous Mobile Robot Fleets

Chavan

Brocanelli

2022

2022 IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS)

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VECMAN: A Framework for Energy-Aware Resource Management in Vehicular Edge Computing Systems

Cited by 18 publications

References 24 publications

Scheduling IoT Applications in Edge and Fog Computing Environments: A Taxonomy and Future Directions

Scheduling IoT Applications in Edge and Fog Computing Environments: A Taxonomy and Future Directions

Green Internet of Vehicles (IoV) in the 6G Era: Toward Sustainable Vehicular Communications and Networking

Towards High-Quality Battery Life for Autonomous Mobile Robot Fleets

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