This paper proposes a novel contention window control scheme for backoff based CRA (Collision Resolution Algorithm). The proposed scheme demonstrates a distributed way to control random slot selection over the contention window in each contention stage with reference to normalized backoff value in the previous contention stage. Such control results an intelligent backoff time distribution over the contention window for each contention stage. Backoff time chosen for every access from such distribution potentially mitigates much collisions along with reduced channel ideal time. Analysis results show that, compared to the performance of legacy scheme incorporating DSSS (Direct Sequence Spread Spectrum) 802.11b system parameters, there is at least 13% normalized throughput enhancement with heavily reduced packet delay in an IBSS (Independent Basic Service Set) with more than 30 stations with saturated traffic.

Several TCPs have been proposed to cope with the change of networks. They have mainly focused on modifying congestion control. However, even ideal congestion control for wireless networks cannot achieve remarkable throughput increase. In this paper, we verify that the reason for this exists in a vulnerable point where existing loss recovery algorithms do not consistently work as packet loss rate increases due to ack starvation during loss recovery. In this paper, we propose a novel loss recovery algorithm using packet transmission order, which shows a steady loss recovery ability even though packet loss rate increases. This leads to significant throughput increase of wireless TCP.

Due to its topological generality and flexibility, the k-ary n-cube architecture has been actively researched for various applications. However, the processor allocation problem has not been adequately addressed for the k-ary n-cube architecture, even though it has been studied extensively for hypercubes and meshes. The earlier k-ary n-cube allocation schemes based on conventional slice partitioning suffer from internal fragmentation of processors. In contrast, algorithms based on job-based partitioning alleviate the fragmentation problem but require higher time complexity. This paper proposes a new allocation scheme based on isomorphic partitioning, where the processor space is partitioned into higher dimensional isomorphic subcubes. The proposed scheme minimizes the fragmentation problem and is general in the sense that any size request can be supported and the host architecture need not be isomorphic. Extensive simulation study reveals that the proposed scheme significantly outperforms earlier schemes in terms of mean response time for practical size k-ary and n-cube architectures. The simulation results also show that reduction of external fragmentation is more substantial than internal fragmentation with the proposed scheme.