Book Chapter10.1007/978-981-10-6427-2_36
Optimization Using Swarm Intelligence and Dynamic Graph Partitioning in IoE Infrastructure: Fog Computing and Cloud Computing
Subhrapratim Nath,Arnab Seal,Titir Banerjee,Subir Kumar Sarkar +3 more
- 24 Mar 2017
- pp 440-452
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TL;DR: This paper aims to resolve some of the issues so faced by the IoE paradigm, with the help of meta-heuristics and to incorporate proper swarm intelligence based routing algorithms to optimize connection issues such as real time delay, network congestion.
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Abstract: The modern society, with the advances in wireless sensor network (WSN) technology, are connected in ways more than one. Since the evolution of evolutionary computing and the Internet of Everything (IoE), the term connected has faced a more significant meaning per se. But as the IoE grows, it becomes more complicated and tackling its complications in various aspects of its architecture becomes all the more paramount. This paper aims to resolve some of the issues so faced by the IoE paradigm, with the help of meta-heuristics and to incorporate proper swarm intelligence based routing algorithms to optimize connection issues such as real time delay, network congestion. Fog Computing is used to distribute the workload and to optimize the utilization of bandwidth, which maintains a clean and efficient channel of communication between the IoE clusters and the primary cloud storage. In this approach a new algorithm based on Directed Artificial Bat Algorithm (DABA) is deployed and Particle Swarm Optimization (PSO) meta-heuristics is used to optimize the capabilities of the IoE cluster and maintain its density. The Fog servers, so implemented, grapple with the increased mobility and network usage using the Dynamic Graph Partitioning algorithm.
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Citations
Distributed Artificial Intelligence-as-a-Service (DAIaaS) for Smarter IoE and 6G Environments.
TL;DR: A framework for Distributed AI as a Service (DAIaaS) provisioning for Internet of Everything (IoE) and 6G environments is proposed to facilitate standardization of distributed AI provisioning, allow developers to focus on the domain-specific details without worrying about distributed training and inference, and help systemize the mass-production of technologies for smarter environments.
98
Load balancing techniques for fog computing environment: Comparison, taxonomy, open issues, and challenges
Vijaita Kashyap,Ashok Kumar +1 more
TL;DR: In this survey, several algorithms have been discussed that are based on LB, which works out the issue of overloaded data on the network and some parameters that authors have focused in LB are latency, bandwidth, deadlines, cost, security, execution time, and response time.
10
Performance analysis of gas sensing device and corresponding IoT framework in mines
TL;DR: An IoT frame work has been proposed in this study where Node MCU (ESP8266) is used as a WiFi module along with Message Queuing Telemetry Transport protocol, which resulted in better speed and efficiency.
9
Survey on Load balancing in fog computing in smart healthcare system
Hayder Makki Shakir,Jaber Karimpour +1 more
TL;DR: This study surveys load balancing techniques in fog computing for smart healthcare systems, highlighting the importance of efficient resource allocation in healthcare applications where timely and accurate services directly impact patient outcomes and quality of life.
Composite Technology Challenge System for Optimization in 5G Communications
Mark Sh. Levin
- 01 Jul 2020
TL;DR: In the article, a modular technology challenge system is proposed as a basis for the system improvement process and the combinatorial framework is described, based on morphological design.
References
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Flavio Bonomi,Rodolfo A. Milito,Preethi Natarajan,Jiang Zhu +3 more
- 01 Jan 2014
TL;DR: This chapter proposes a hierarchical distributed architecture that extends from the edge of the network to the core nicknamed Fog Computing, and pays attention to a new dimension that IoT adds to Big Data and Analytics: a massively distributed number of sources at the edge.
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