By investigating flow level characteristics of Internet traffic, we are able to trace the root of load imbalance in hash-based load-splitting schemes. We model flow popularity distributions as Zipf-like and prove that under typical Internet traffic mix, a hash scheme cannot balance workload statistically, not even in the long run. We then develop a novel load-balancing packet scheduler for para...

Background: There are different street substance users' communities (SSUCs). Typology of SSUCs in Tehran, Iran was approached in this qualitative study.Methods: Using content analysis and saturation principles, 22 street-outreach workers were recruited and interviewed. Data were analyzed using open, axial, and selective coding.Findings: Three types of SSUCs were identified. SSUCs were different...

Abstract Breakthroughs in AI are accelerating global commercial competition and transforming the international security environment. The reach influence of foreign-based network platforms present risks to American society require us confront questions about their origin purpose. Meanwhile, technologies enhancing several existing national threats, will change way states try gain leverage against...

Today, cloud computing applications are rapidly constructed by services belonging to different cloud providers and service owners. This work presents the inter-cloud elasticity framework, which focuses on cloud load balancing based on dynamic virtual machine reconfiguration when variations on load or on user requests volume are observed. We design a dynamic reconfiguration system, called inter-...

Cloud scale load balancers, such as Ananta and Duet are critical components of the data center (DC) infrastructure, and are vital to the performance of the hosted online services. In this paper, using traffic traces from a production DC, we show that prior load balancer designs incur substantial overhead in the DC network bandwidth usage, due to the intrinsic nature of traffic redirection. More...