2996684
Impact of location inconsistencies on geographic routing in wireless networks
Recently, geographic routing in wireless networks has gained attention due to several advantages of location information. Location information eliminates the necessity to set up and maintain explicit routes. These advantages allow scalability especially in dynamic and unstable wireless networks. However, no matter which technologies or techniques a location system uses, its measurements will have some amount of quantifiable inaccuracy depending on environment and system. These inaccuracies may affect the performance and even correctness of geographic routing. However, thus far, these impacts have not been studied in-depth. In this paper, we analyze the impact of location inaccuracy on geographic routing. Our study shows the significant impact of location inaccuracy on the performance of geographic routing in terms of packet drops, non-optimal paths and routing loops.
7491965
Modeling and analyzing the impact of location inconsistencies on geographic routing in wireless networks
Recently, geographic routing in wireless networks has gained attention due to several advantages of location information. Location information eliminates the necessity to set up and maintain explicit routes, which reduces communication overhead and routing table size. These advantages allow scalability especially in dynamic and unstable wireless networks. However, no matter which technologies or techniques a location system uses, its measurements will have some amount of quantifiable inaccuracy depending on environment and system. These inaccuracies may affect the performance and even correctness of geographic routing. However, thus far, these impacts have not been studied in-depth. In this paper, we analyze the impact of location inaccuracy on geographic routing. First, we model location inaccuracy metrics - absolute location inaccuracy, relative distance inaccuracy, absolute location inconsistency and relative distance inconsistency. Then, we analyze how location inaccuracy metrics affect the building blocks of geographic routing including greedy forwarding and local maximum resolution. We use extensive NS-2 simulations to evaluate the performance of geographic routing using a wide array of parameter settings including inaccuracy level, node degree and network diameter. In our simulation results, reasonable location inaccuracy (of 20 percent or less of radio range) caused packet drop reaching up to 54 percent, non-optimal path up to 53 percent and packet looping. These observations indicate the importance of re-visiting geographic routing protocols, and the significance of considering location inaccuracy in their design and evaluation.
6995681
Quasi-optimal case-selective neural network model for software effort estimation
Abstract A number of software effort estimations have attempted using statistical models, case based reasoning, and neural networks. The research results showed that the neural network models perform at least as well as the other approaches, so we selected the neural network model as the estimator. However, since the computing environment changes so rapidly in terms of programming languages, development tools, and methodologies, it is very difficult to maintain the performance of estimation models for the new breed of projects. Therefore, we propose a search method that finds the right level of relevant cases for the neural network model. For the selected case set, the scale of the neural network model can be reduced by eliminating the qualitative input factors with the same values. Since there exist a multitude of combinations of case sets, we need to search for the optimal reduced neural network model and corresponding case set. To find the quasi-optimal model from the hierarchy of reduced neural network models, we adopted the beam search technique and devised the case-set selection algorithm. We have shown that the resulting model significantly outperforms the original full model for the software effort estimation. This approach can be also used for building any case-selective neural network.
17318532
Enhancement of a WLAN-Based Internet Service
A wireless LAN (WLAN)-based Internet service, called NESPOT, of Korea Telecom (KT), the biggest telecommunication and Internet service company in Korea, has been operational since early 2002. As the numbers of subscribers and deployed access points (APs) increase, KT has been endeavoring to improve its service quality as well as the network management. In this paper, we introduce a joint effort between Seoul National University (SNU) and KT to achieve it. We have been addressing two major issues as part of the joint project thus far: (1) a unified WLAN management/maintenance tool; and (2) real-time traffic support enhancement. We present our on-going efforts as well as some preliminary results. Some issues, which need further attention for the future NESPOT service enhancement, are also introduced.
10209884
Downlink power allocation for multi-class wireless systems
In this paper we consider a power allocation problem in multi-class wireless systems. We focus on the downlink of the system. Each mobile has a utility function that characterizes its degree of satisfaction for the received service. The objective is to obtain a power allocation that maximizes the total system utility. Typically, natural utility functions for each mobile are nonconcave. Hence, we cannot use existing convex optimization techniques to derive a global optimal solution. We develop a simple (distributed) algorithm to obtain a power allocation that is asymptotically optimal in the number of mobiles. The algorithm is based on dynamic pricing and consists of two stages. At the mobile selection stage, the base station selects mobiles to which power is allocated. At the power allocation stage, the base station allocates power to the selected mobiles. We provide numerical results that illustrate the performance of our scheme. In particular, we show that our algorithm results in system performance that is close to the performance of a global optimal solution in most cases.
1514436
Dynamic monitoring of high-performance distributed applications
Developers and users of high-performance distributed systems often observe performance problems such as unexpectedly low throughput or high latency. Determining the source of the performance problems requires detailed end-to-end instrumentation of all components, including the applications, operating systems, hosts, and networks. However, one must be very careful to design the instrumentation to have extremely low overhead, and not affect the system being monitored. In this paper we present a very light-weight instrumentation system that can be dynamically activated to unobtrusively collect and aggregate detailed end-to-end monitoring information from distributed applications. We also show how emerging "web services" can be used to facilitate remote interaction with this system.
19612327
Instruction level redundant number computations for fast data intensive processing in asynchronous processors
Instruction level parallelism (ILP) is strictly limited by various dependencies. In particular, data dependency is a major performance bottleneck of data intensive applications. In this paper we address acceleration of the execution of instruction codes serialized by data dependencies. We propose a new computer architecture supporting a redundant number computation at the instruction level. To design and implement the scheme, an extended data-path and additional instructions are also proposed. The architectural exploitation of instruction level redundant number computations (IL-RNC) makes it possible to eliminate carry propagations. As a result execution of instructions which are serialized due to inherent data dependencies is accelerated. Simulations have been performed with data intensive processing benchmarks and the proposed architecture shows about a 1.2-1.35 fold speedup over a conventional counterpart. The proposed architecture model can be used effectively for data intensive processing in a microprocessor, a digital signal processor and a multimedia processor.