Cloud-Assisted Edge Computing: Joint Computation Offloading and Bandwidth Assignment PROJECT TITLE : Joint Computation Offloading and Bandwidth Assignment in Cloud-Assisted Edge Computing ABSTRACT: The process of augmenting the computational capabilities of mobile devices with limited resources by offloading computation based on mobile edge computing paradigms is called mobile offloading. However, the performance improvement that can be achieved through computation offloading is limited by the capacity limitations of edge servers. In this piece, we take into consideration a three-tiered computation offloading schema that includes multiple users, edge servers, and cloud servers. Offloading computation from mobile devices to edge servers or, if necessary, further offloading to remote cloud servers allows for more processing power to be made available. Because a number of mobile devices that are connected to edge servers will share a common wireless Communication network that may contain uplink and downlink channels, the allocation of bandwidth for the channels also places constraints on the performance improvement that can be achieved through computation offloading. Both the problem of how to determine the offloading strategy and the problem of how to assign the bandwidth are jointly studied and formulated as a programming problem in this article with the goal of reducing the typical amount of time it takes for an application to respond. After conducting an analysis on the joint problem, we proceed to modify it so that it is a piecewise convex programming problem. An effective algorithm that can locate the best possible solution is what we suggest developing. Extensive testing demonstrates that our algorithm is significantly more effective than other algorithms that have come before it. The results of the experiments demonstrate, in addition, that the functionality of our algorithm is extremely dependable. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest Joint MapReduce Scheduling and Network Policy Optimization in Hierarchical Data Centers Using Fog Computing to Improve the Scheduling of Real-Time Tasks