TCP is most widely used transport layer protocol. Most of the applications such as e-mails, file transfers use TCP due to its reliable communication. There are various mechanisms to control the congestion in the network. The variants of TCP implement slow start, congestion avoidance, fast retransmit and fast recovery algorithms in different ways for congestion control. In this paper, we have simulated four TCP variants namely Tahoe, Reno, New-Reno and Vegas in mobile ad hoc network over AODV and DSR routing protocols. Simulation is done in NS2. Comparison of throughput, end-to-end delay and packet delivery fraction is made against pause time and node speed variation to determine the performance of these four TCP congestion control algorithms.

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Optimizing user experience for streaming video applications on handheld devices is a significant research challenge. In this paper, we propose an integrated power management approach that unifies low level architectural optimizations (CPU, memory, register), OS power-saving mechanisms (Dynamic Voltage Scaling) and adaptive middleware techniques (admission control, optimal transcoding, network traffic regulation). Specifically, we identify interaction parameters between the different levels and optimize them to significantly reduce power consumption. With knowledge of device configurations, dynamic device parameters and changing system conditions, the middleware layer selects an appropriate video quality and fine tunes the architecture for optimized delivery of video. Our performance results indicate that architectural optimizations that are cognizant of user level parameters(e.g. transcoded video quality) can provide energy gains as high as 57.5% for the CPU and memory. Middleware adaptations to changing network noise levels can save as much as 70% of energy consumed by the wireless network interface. Furthermore, we demonstrate how such an integrated framework, that supports tight coupling of inter-level parameters can enhance user experience on a handheld substantially.

In distributed environments, generic middleware services(e.g. caching, location management etc.) are widely used to satisfy application needs in a cost-effective manner. Such middleware services consume system resources such as storage, computation and communication and can be sources of significant power overheads when executed on low-power devices. We present a distributed middleware framework( parm), that is inherently power-aware and reconfigures itself to adapt to diminishing power levels of low-power devices. In this paper, we i) determine whether a reconfigurable component-based middleware framework can be utilized to achieve energy gains in low-power devices, while preserving the semantics of the middleware services, ii) present and evaluate a graph theoretic approach for dynamically determining middleware component reconfigurations and ascertaining the optimal frequency at which the restructuring should occur, for maximal energy gains at the device. We use extensive profiling to chart the energy usage patterns of middleware components and applications, and use the profiled data to drive our reconfiguration decisions. Our simulation results demonstrate that our framework is able to save 5% to 35% of energy depending on the nature and class of applications and middleware components used.