Abstract-Security has become a critical factor in today's computation systems. The security threats that risk our confidential information can come in form of seemingly legitimate client request to server. While illegitimate requests consume the number of connections a server can handle, no valid new connections can be made. This scenario, named SYNflooding attacks can be controlled through a fair scheduling algorithm that provides more opportunity to legal requests. This paper proposes a detailed scheduling approach named Largest Processing Time Rejection-Particle Swarm Optimization (LPTR-PSO) that defends the server against varying intensity SYN-flood attack scenarios through a three-phased algorithm. This novel approach considers the number of half-open connections in the server buffer and chooses a phase accordingly. The simulation results show that the proposed defense strategy improves the performance of under attack system in terms of memory occupancy of legal requests and residence time of attack requests.
Abstract-Cloud Computingensures Service Level Agreement (SLA) by provisioning of resources to cloudlets. This provisioning can be achieved through scheduling algorithms that properly maps given tasks considering different heuristics such as execution time and completion time. This paper is built on the concept of max-min algorithm with and unique proposed modification. A novel idea of clustering based max-min scheduling algorithm is introduced to decrease overall makespan and better VM utilization for variable length of the tasks. Experimental analysis shows that due to clustering, it provides better result than the different variations of max-min as well as other heuristics algorithm in terms of effective utilization of faster VMs and proper scheduling of tasks considering all possible scheduling scenarios and picking up the best solution.
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