| Title |
Towards energy efficient Smart city services: A software defined resource management scheme for data centers |
| ID_Doc |
41961 |
| Authors |
Reddy, KHK; Luhach, AK; Kumar, VV; Pratihar, S; Kumar, D; Roy, DS |
| Title |
Towards energy efficient Smart city services: A software defined resource management scheme for data centers |
| Year |
2022 |
| Published |
|
| Abstract |
With the rapid advancements in the services computing paradigm, cloud computing has been a fundamental requirement for enabling practically all sophisticated applications and services, particularly for Smart cities. However curbincs energy dissipation in the data centers (DC) has been a key effort, albeit while fulfilling the quality of service (QoS) requirement of DCs are characterized by complex interconnections among their servers. Maintenance of these servers under dynamic scenarios while ensuring scalability and performance demands Software Defined Networks (SDNs) for easy and efficient resource management. This paper addresses the QoS requirement and energy-efficient operation for Software-Defined DCs for resource management by means of (i) selectively activating a subset of switches, (ii) propounding multi-path routing for all scheduled flows, (iii) aggregating data and routing structure to avoid network congestion and (iv) installation of appropriate forwarding rules across the network switches. These issues are collectively put together in the outline of ILP problem, but due to its computational complexity, a heuristic optimization approach called particle swarm intelligence is articulated. The particle swarm intelligence (PSI) algorithm is employed for feature selection to obtain the minimum cost of the generated energy while satisfying the network traffic demand. The presented simulation result lay the efficacy of the proposed algorithm. |
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