International Journal of Smart Grid and Green Communications
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International Journal of Smart Grid and Green Communications (4 papers in press)
PERFORMANCE EVALUATION OF ENERGY AWARE QOS ENABLED ROUTING PROTOCOL FOR WIRELESS MESH NETWORKS by Mallikarjuna Rao Yamarthy, M.V. Subramanyam, K.Satya Prasad Abstract: This paper proposes a energy aware routing protocol for wireless mesh network (WMNs). The inherent properties of WMNs such as robustness, multi-hop communication and easy deployment draws attention of the researchers and industrialists. The WMNs became the usual choice for communication set up in the applications of military and disaster management. In disaster management and military applications the communication has to set up in quick time with ease. This can be accomplished using WMNs. In such applications and scenarios the mesh nodes may not expect the fixed power supply connections for their normal operation. Hence, mesh nodes may rely on ambient energy. The ambient energy could be from solar or wind. In such cases, the nodes may not contain energy all the time for their operation. In such untenable cases, we require energy aware routing protocols to prevent deterioration of the network performance due to power outages of the nodes. This paper proposes energy aware QoS enabled routing protocol (EAQER) based on the node weight and path preference probability. The EAQER is analysed and shown superior performance compared to baseline routing protocols in terms of throughput, end to end delay, jitter and packet delivery ratio. Keywords: Node weight;path preference probability; quality of service; routing; wireless rnmesh networks.
Osmosis machine learning load balancing of healthcare tasks in cutting edge technologies with smart grid by Basetty Mallikarjuna Abstract: The Smart grid communication requires an embedded approach on IoT-based cloud, fog computing and big data. In order to provide e-health and m-health services, the allocation of tasks on resources in healthcare services is crucial. The primary need for users in the healthcare industry is the solution to the bottleneck of service level agreement (SLA) and accomplishes the quality of service (QoS) parameters. The add-on objective is to achieve effective resource utilization and satisfaction of the end-user application for effective communication and load balancing of tasks on cutting edge technologies. The machine learning approach in osmosis load balancing of tasks at the end of the fog service provider (FSP) level reduces the network utilization time, latency, usage of energy, etc. and the results proves that fog nodes are efficient than the cloud nodes, and also the experimental results proved that the proposed model is efficient than various other existing approaches. Keywords: smart grid; IoT-based cloud; big data; e-health; electronic health;
m-health; ML approach on osmosis; fog service provider; FSP; latency; usage
of energy. DOI: 10.1504/IJSGGC.2020.10032101
An effective management of scheduling-tasks by using MPP and MAP in smart grid by Basetty Mallikarjuna Abstract: In smart grid environment, the integrated service of IoT-based cloud infrastructure has various applications to improve the QoS parameters to achieve the service level agreement (SLA). Allocation of task at the end of the fog service provider (FSP) invites the scheduling queue and sets priority. The task is allocated into the fog nodes, when a task arrives into the scheduling queue. Markovian arrival process (MAP) and Markovian poison process (MPP) with partial buffer shares mechanism, computes with probabilities and classify them based on the priority. The arriving of tasks on scheduling queue is through MAP, and the allocation of tasks to the fog nodes is through MPP. The method of Markovian self-similar networks is followed for non-priority tasks and it is also allocated to the fog nodes. The tasks arrive at the scheduling queue is based on priority. It also calculates the probability of task allocated to the fog nodes using MPP for effective schedule management.
Keywords: Markovian arrival process; MAP; Markovian poison process; MPP; fog service provider; FSP; service level agreement; SLA; priority tasks; non-priority tasks; fog nodes; IoT-based cloud; smart grid. DOI: 10.1504/IJSGGC.2020.10033422
The effective tasks management of workflows inspired by NIM-game strategy in smart grid environment by Basetty Mallikarjuna Abstract: In smart grid environment incorporated with IoT-based cloud infrastructure, management of efficiency is a paradigm. This procedure considers an adversary search technique (ADVST). It approaches the MINIMAX algorithm on virtual machines for management of workflows in IoT-based cloud infrastructure, which is named as a VMMINMAX algorithm. The algorithm finds the over-loaded-tasks group named as VMMAXIMISER. The under-loaded-tasks group named as VMMINIMISER and the balanced-tasks group named as VMBALANCED. The VMMINMAX algorithm is used for effective tasks
management strategy and it can be achieved, by moving the workflows from heavily-loaded-VMs to low-loaded-VMs. It balances over VMs as VMBALANCED and reduces the non-critical-workflow-tasks and effective allocation of critical-workflow-tasks, with respect to make-span and average make-span of VMs. The algorithm have been tested with different parameters such as throughput, overhead, resource utilisation, response time, scalability and performance and proved. Keywords: adversary search technique; virtual machine; VMMINMAX algorithm; VMMAXIMISER group; VMMINIMISER group; VMBALANCED group. DOI: 10.1504/IJSGGC.2020.10033423