SRAA: A Load Distribution Policy to manage the Resources Dynamically in a Smart City
Priya Matta1, Bhasker Pant2, Sachin Sharma3
1Priya Matta*, Department of Computer Science and Engineering, Graphic Era Deemed to be University, Dehradun, Uttarakhand, India.
2Bhasker Pant, Department of Computer Science and Engineering, Graphic Era Deemed to be University, Dehradun, Uttarakhand, India.
3Sachin Sharma, Department of Computer Science and Engineering, Graphic Era Deemed to be University, Dehradun, Uttarakhand, India.
Manuscript received on November 13, 2019. | Revised Manuscript received on 21 November, 2019. | Manuscript published on December 10, 2019. | PP: 5035-5041 | Volume-9 Issue-2, December 2019. | Retrieval Number: B7685129219/2019©BEIESP | DOI: 10.35940/ijitee.B7685.129219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: There are a variety of buzz words linked to advanced technology and technological developments in the modern era, out of which the world is primarily geared towards the Internet of Things. It is a network of things and devices capable of communicating with each other as well as connecting to the Internet, these devices are also embedded with the capabilities of electronics and computing. IoT is a smart city once incorporated with a city. A Smart City’s architecture and growth has its own challenges. In addition to the other technological and social challenges, resource management is one of the most critical obstacles in achieving effective and seamless smart city execution. Load balancing is one of asset management’s major components. Our research addressed the idea of IoT and a smart society with regard to a smart city, inspiration and challenges. The work proposed focuses on balancing the load in a smart city. Our main contribution is an algorithm for balancing the load in a smart city between different resource providers. SRAA has two variants in the proposed algorithm, which are explained. The algorithm modifications are performed using two case studies. The algorithm provided is suitable for a dynamic environment.
Keywords: Internet of Things, Smart City, Resources Management, Load Balancing, SRAA.
Scope of the Article: Internet of Things