Zoom Meeting: https://umass-amherst.zoom.us/j/93964404852?pwd=MXU2V3pETm9Ya1VsNndJSlRPdjhjZz09
Abstract:
The past few years have witnessed significant growth in the use of a large number of smart devices, computational and storage resources. These devices and resources distributed over a physical space are collectively called a distributed service network. One of the new applications closely related to a distributed service network is the internet of things (IoT). Efficient resource allocation for such high performance IoT system remains one of the most critical problem. Delivering content generated from the deployed smart devices to users with a low response time and assigning users or applications to various resources are important to sustained high performance of the distributed service network.
In this proposal, we model and optimize the allocation of resources in a distributed service network. First, we develop analytical tools for an edge caching architecture to reduce the response time for delivering content to the end user. To this end, we study the utility optimization of content placement at edge caches through timer-based (TTL) policies. We develop provably optimal distributed algorithms that operate at each network cache to maximize the overall network utility. Our TTL-based optimization model provides theoretical answers to how long each content must be cached, and where it should be placed in the edge network.
Next, we develop and evaluate assignment policies that allocate resources to users, where both resources and users are located on a one-dimensional line. We consider unidirectional assignment policies that allocate resources only to users located to their left. We show that when user and resource locations are modeled by statistical point processes, the spatial system under unidirectional policies can be mapped into bulk service queueing systems, thus allowing the application of many queueing theory results that yield closed form expressions. We also consider bidirectional policies where there are no directional restrictions on resource allocation and develop an algorithm for computing the optimal assignment which is more efficient than known algorithms in the literature when there are more resources than users. Numerical evaluation of performance of unidirectional and bidirectional allocation schemes yields design guidelines beneficial for resource placement. A through analysis of a two dimensional spatial system remains one of our future works.
Advisor: Don Towsley