Optimizing Operation of a Hierarchical Campus-wide Mobile Grid for Intermittent Wireless Connectivity

Κατσαρός, Κωνσταντίνος; Polyzos, George C.

doi:10.1109/lanman.2007.4295984

Cited by 16 publications

(14 citation statements)

References 15 publications

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“…But mobile devices at present have severe limitations in terms of processing, memory capabilities and energy (Litke et al 2004). Due to the limitation, their integration into the Grid as resource providers is difficult (Hummel and Jelleschitz 2007;Otebolaku et al 2007;Vetri Selvi et al 2007;Katsaros and Polyzos 2007). Minimizing the energy usage in mobile devices poses significant challenges in mobile grid.…”

Section: Related Work and Motivationsmentioning

confidence: 99%

“…These limitations in mobile devices impose great difficulties to provide users as an option to solve complex problems when using these devices. Some studies argue that because mobile devices are resource constrained, they should be incorporated in a grid only as resource consumers (Katsaros and Polyzos 2007). But, mobile devices are increasingly becoming powerful (mostly in terms of computational power and storage) to also participate in grid systems as resource providers.…”

Section: Introductionmentioning

confidence: 99%

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Collaboration among mobile agents for efficient energy allocation in mobile grid

2011

Inf Syst Front

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The use of mobile devices in grid environments may have two interaction aspects: devices are considered as users of grid resources or as grid resources providers. Due to the limitation constraints on energy and processing capacity of mobile devices, their integration into the Grid is difficult. In this paper, we investigate the cooperation among mobile devices to balance the energy consumption and computation workloads. Mobile devices can have different roles such as buyer devices and seller devices. In the mobile grid, the energies of mobile devices are uneven, energy-poor devices can exploit other devices with spare energy. Our model consists of two actors: A buyer device agent represents the benefits of mobile buyer device that intends to purchase energy from other devices. A seller device agent represents the profits of mobile seller device that is willing to sell spare energy to other devices. The objective of optimal energy allocation in mobile grid is to maximize the utility of the system without exceeding the energy capacity, expense budget and the deadline. A collaboration algorithm among mobile agents for efficient energy allocation is proposed. In the simulation, the performance evaluation of collaboration algorithm among mobile agents is conducted.

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Section: Related Work and Motivationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Collaboration among mobile agents for efficient energy allocation in mobile grid

2011

Inf Syst Front

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“…Only very recently, however, have specific scheduling strategies for wireless and mobile ad hoc grids emerged in the literature 17,25,30,20,49 . Most of them employ task replication to optimize some objective function related to the inherent limitations in processing, memory, battery power, and wireless communications capabilities of mobile devices.…”

Section: Resource Schedulingmentioning

confidence: 99%

“…The proxy runs a revised Min-Min heuristic algorithm, which aims at minimizing energy consumption at the mobile nodes. A similar approach based on hierarchical scheduling is proposed by Katzaros and Polyzos 25 , with the difference that task replication is employed to treat disconnection events. Both approaches are inadequate for mobile ad hoc grids due to the need for a fixed node acting as the scheduler.…”

Section: Resource Schedulingmentioning

confidence: 99%

Performance evaluation of a discovery and scheduling protocol for multihop ad hoc mobile grids

et al. 2009

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Despite the many research efforts addressing the integration of mobile nodes into grids, only a few of them have considered the establishment of mobile grids over wireless ad hoc networks (hereafter, mobile ad hoc grids). Clearly, such grids need specialized resource discovery and scheduling mechanisms. To the best of our knowledge, though, the research on these mechanisms for mobile ad hoc grids is still preliminary. Besides, and more importantly, it has approached discovery and scheduling as separate mechanisms, which, we argue, is not suitable for mobile ad hoc grids. In this paper, we propose the integration of resource discovery and scheduling for mobile ad hoc grids into a single protocol called DICHOTOMY (DIscovery and sCHeduling prOTOcol for MobilitY). This protocol allows computational tasks to be distributed appropriately in a mobile ad hoc grid, while mitigating the overhead of discovery messages exchanged among the nodes. Our experiments show that the protocol: (i) does proper scheduling, allowing an efficient load balancing among the nodes and helping with lowering the average completion time of tasks; (ii) keeps the discovery efficiency at acceptable levels in mobility scenarios and (iii) scales very well with respect to an increasing number of nodes, both in the total amount of energy savings due to packet transmissions and the distribution of such savings among the nodes.

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“…De acordo com Katsaros & Polyzos (2007), provisão de recursos móveis pode ser realizada considerando-se duas arquiteturas fundamentalmente distintas: grades móveis on-site e grades móveis ad hoc.…”

Section: Dispositivos Móveis Como Provedores De Recursosunclassified

Escalonamento em grades móveis: uma abordagem ciente do consumo de energia

Borro¹

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Optimizing Operation of a Hierarchical Campus-wide Mobile Grid for Intermittent Wireless Connectivity

Cited by 16 publications

References 15 publications

Collaboration among mobile agents for efficient energy allocation in mobile grid

Collaboration among mobile agents for efficient energy allocation in mobile grid

Performance evaluation of a discovery and scheduling protocol for multihop ad hoc mobile grids

Escalonamento em grades móveis: uma abordagem ciente do consumo de energia

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