International journal of innovative technology and exploring engineering, Sep 30, 2019
Fog computing is one of the enabling computing technology which primarily aims to fulfill the req... more Fog computing is one of the enabling computing technology which primarily aims to fulfill the requirements of the Internet of Things (IoT). IoT is fast-growing networking and computing sector. The scalability of users, devices, and application is crucial for the success of IoT systems. The load balancing is an approach to distribute the load among computing nodes so that the computing nodes are not overloaded. In this paper, we propose the priority-based request servicing at fog computing centers. We particularly address the situation when the fog node in fog computing center (FCC) receives more workload than their capacity to handle it. The increased workload is shifted to nearby fog nodes rather than to the remote cloud. The proposed approach is able to minimize the offloading the high priority request to other nodes by 11% which proves the novelty of our proposed.
With advancements in communications and sensor technologies Internet of Things (IoT) is witnessin... more With advancements in communications and sensor technologies Internet of Things (IoT) is witnessing rapid growth in this decade. IoT is a complex system consisting of variety of sensing devices, network protocols, connecting networks, and architectures etc. Middleware is well known approach to cope up with the complexities inherent in building IoT system. Middleware is software component which helps in developing scalable IoT system, integrating data from variety of IoT devices, offering security, discovering service, providing sensor data analytics, context awareness etc. In this paper, we present the necessity of middleware along with requirement it should addresses for IoT. Followed by survey of middlewares which are relevant to IoT using identified requirements. We also discuss challenges and possible directions for future research.
International Journal of Advanced Networking and Applications
The Internet of Things (IoT) extends the Internet wherein real world things are part of a computi... more The Internet of Things (IoT) extends the Internet wherein real world things are part of a computing network. The IoT has seen exponential growth and according to Cisco prediction about 50 billion devices will be connected by 2020. Handling this massive scale is challenging research issue. In this paper, we use cloud-fog-edge based IoT middleware for distributed IoT service provisioning. We model IoT middleware using queueing network, perform analytical analysis of IoT middleware components. Followed by dynamic scaling algorithm which considers contention and coherency as limiting factors for scalability. It is used for quantitative analysis of IoT middleware with the increasing workload. The scalability function was evaluated using the simulation for important performance and scalability parameters namely throughput, CPU utilization and response time. It is observed that because of contention and coherency overhead, the proposed approach is able to scale sub-linearly which is practical compared ideal scalability of multi-server queueing network and not very restrictive as given universal scalability law(USL) applied for tightly coupled systems.
International Journal of Advanced Networking and Applications, 2019
The Internet of Things (IoT) extends the Internet wherein real world things are part of a computi... more The Internet of Things (IoT) extends the Internet wherein real world things are part of a computing network. The IoT has seen exponential growth and according to Cisco prediction about 50 billion devices will be connected by 2020. Handling this massive scale is challenging research issue. In this paper, we use cloud-fog-edge based IoT middleware for distributed IoT service provisioning. We model IoT middleware using queueing network, perform analytical analysis of IoT middleware components. Followed by dynamic scaling algorithm which considers contention and coherency as limiting factors for scalability. It is used for quantitative analysis of IoT middleware with the increasing workload. The scalability function was evaluated using the simulation for important performance and scalability parameters namely throughput, CPU utilization and response time. It is observed that because of contention and coherency overhead, the proposed approach is able to scale sub-linearly which is practical compared ideal scalability of multi-server queueing network and not very restrictive as given universal scalability law(USL) applied for tightly coupled systems.
The neural key exchange algorithm for choosing the relevant inputs is sufficient to achieve a mor... more The neural key exchange algorithm for choosing the relevant inputs is sufficient to achieve a more or less secure key-exchange protocol, however A and B could improve it by taking more information into account, including queries in the training process of the neural networks. Alternatively A and B are generating an input which is correlated with its state and A or B is asking the partner for the corresponding output bit[7].
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Papers by Dilip T Rathod