Year: 2018
Type: conference-abstract
Abstract: We establish a unified analytical framework for designing load balancing algorithms that can simultaneously achieve low latency, low complexity, and low communication overhead. We first propose a general class ¶ of load balancing policies and prove that they are both throughput optimal and heavy-traffic delay optimal. This class ¶ includes popular policies such as join-shortest-queue (JSQ) and power-of- d as special cases, but not the recently proposed join-idle-queue (JIQ) policy. In fact, we show that JIQ is not heavy-traffic delay optimal even for homogeneous servers. By exploiting the flexibility offered by the class ¶, we design a new load balancing policy called join-below-threshold (JBT-d), in which the arrival jobs are preferentially assigned to queues that are no greater than a threshold, and the threshold is updated infrequently. JBT-d has several benefits: (i) JBT-d belongs to the class ¶i and hence is throughput optimal and heavy-traffic delay optimal. (ii) JBT-d has zero dispatching delay, like JIQ and other pull-based policies, and low message overhead due to infrequent threshold updates. (iii) Extensive simulations show that JBT-d has good delay performance, comparable to the JSQ policy in various system settings.
Authors: Xingyu Zhou, Fei Wu, Jian Tan, Yin Sun, Ness Shroff
Institutions: The Ohio State University, Auburn University
Language: English
Subfield: Management Information Systems
Domain: Social Sciences
Open Access status: bronze
Awards: G1926678634, G2506819241, CSR: NeTS: Small: Theoretical Foundations for Cache Networks: Performance Models, Algorithms, and Applications, CPS: Synergy: Collaborative Research: Cognitive Green Building: A Holistic Cyber-Physical Analytic Paradigm for Energy Sustainability, ICN-WEN: Collaborative Research: SPLICE: Secure Predictive Low-Latency Information Centric Edge for Next Generation Wireless Networks
OpenAlex ID: W2764200205