Browsing by Author "Youssef, Moustafa A."
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Item Analyzing the Point Coordination Function of the IEEE 802.11 WLAN Protocol using a Systems of Communicating Machines Specification(2002-05-22) Youssef, Moustafa A.; Miller, Raymond E.A model for the specification and analysis of communication protocols called Systems of Communicating Machines is used to specify an IEEE 802.11 Point Coordination Function protocol, and to analyze it for safety and certain restricted liveness properties. The model uses a combination of finite state machines and variables in the specification of each machine, and the communication between machines is accomplished through shared variables. Enabling predicates and actions are associated with each transition; the enabling predicates determine when a transition may be taken, and the actions alter the variable values as the network progresses. One of the advantages which this model has over most other formal description techniques is that simultaneous transitions are allowed. Another advantage is the use of shared variables rather than FIFO queues for communication between machines. This allows the modeling of the shared medium as a single shared variable variable between all communicating processes. Unlike the SDL language which is used in the specification of the 802.11 standard, the Systems of Communicating Machines model is more compact, easier to understand, and easier to analyze for safety and liveness. (Also UMIACS-TR-2002-36)Item On the Optimality of WLAN Location Determination Systems(2003-04-04) Youssef, Moustafa A.; Agrawala, AshokThis paper presents a general analysis for the performance of WLAN location determination systems. In particular, we present an analytical method for calculating the average distance error and probability of error of WLAN location determination systems. These expressions are obtained with no assumptions regarding the distribution of signal strength or the probability of the user being at a specific location, which is usually taken to be a uniform distribution over all the possible locations in current WLAN location determination systems. We use these expressions to find the optimal strategy to estimate the user location and to prove formally that probabilistic techniques give more accuracy than deterministic techniques, which has been taken for granted without proof for a long time. The analytical results are validated through simulation experiments. We also study the effect of the assumption that the user position follows a uniform distribution over the set of possible locations on the accuracy of WLAN location determination systems. The results show that knowing the probability distribution of the user position can reduce the number of access points required to obtain a given accuracy. However, with a high density of access points, the performance of a WLAN location determination system is consistent under different probability distributions for the user position. UMIACS-TR-2003-29Item A Probabilistic Clustering-Based Indoor Location Determination System(2002-04-04) Youssef, Moustafa A.; Agrawala, Ashok; Shankar, A. Udaya; Noh, Sam H.We present an indoor location determination system based on signal strength probability distributions for tackling the noisy wireless channel and clustering to reduce computation requirements. We provide two implementation techniques, namely, Joint Clustering and Incremental Triangulation and describe their tradeoffs in terms of location determination accuracy and computation requirement. Both techniques have been incorporated in two implemented context-aware systems: User Positioning System and the Rover System, both running on Compaq iPAQ Pocket PC's with Familiar distribution of Linux for PDA's. The results obtained show that both techniques give the user location with over 90% accuracy to within 7 feet with very low computation requirements, hence enabling a set of context-aware applications. Also UMIACS-TR-2002-30