Browsing by Author "Kochut, Andrzej"
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Item AD (Attacker Defender) Game(2002-01-31) Kochut, Andrzej; Agrawala, Ashok K.; Larsen, Ronald L.; Shankar, A. UdayaInformation Dynamics is a framework for agent-based systems that gives a central position to the role of information, time, and the value of information. We illustrate system design in the Information Dynamics Framework by developing an intelligence game called AD involving attackers, defenders and targets operating in some space of locations. The goal of the attackers is to destroy all targets. Target destruction takes place when the number of attackers in the target's neighborhood exceeds the number of defenders in this neighborhood by a value WINNING_DIFFERENCE. The goal of defenders is to prevent attackers from achieving their goal. (Also UMIACS-TR-2001-45)Item Rover Technology: Enabling Scalable Location-Aware Computing(2002-01-31) Banerjee, Suman; Agarwal, Sulabh; Kamel, Kevin; Kochut, Andrzej; Kommareddy, Christopher; Nadeem, Tamer; Thakkar, Pankaj; Trinh, Bao; Youssef, Adel; Youssef, Moustafa; Larsen, Ron; Shankar, A. Udaya; Agrawala, AshokLocation-aware computing involves the automatic tailoring of information and services based on the current location of the user. We have designed and implemented Rover, a system that enables location-based services, as well as the traditional time-aware, user-aware and device-aware services. To achieve system scalability to very large client sets, Rover servers are implemented in an "action-based" concurrent software architecture that enables fine-grained application-specific scheduling of tasks. We have demonstrated feasability through implementations for both outdoor and indoor environments on multiple platforms. (Also UMIACS-TR 2001-89)Item Timestep Stochastic Simulation of Computer Networks using Diffusion Approximation(2005-06-23) Kochut, Andrzej; Shankar, A. Udaya; Computer Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Performance evaluation of modern computer networks is challenging because of their large sizes, high speeds of communication links, and complex state-dependent control mechanisms. In particular, TCP congestion control reacts in a nonlinear fashion to the state of the network at the time scale of round-trip times, making analysis intractable. Thus packet-level simulation is the only widely used method of performance evaluation. Although it can be accurate, it is computationally expensive and thus can be applied only to small networks and low link speeds. Timestep Stochastic Simulation (TSS) is a novel method for generating sample paths of computer networks, in increments of time steps rather than packet transmissions. TSS has a low computation cost independent of packet rates and provides adequate accuracy for evaluating general state-dependent control mechanisms. TSS generates the evolution of the system state S(t) on a sample path in time steps of size delta. At each step, S(t + delta) is randomly chosen according to S(t) and the probability distribution Pr[S(t+delta)|S(t)], obtained using the diffusion approximation. Because packet transmission and reception events are replaced by time steps, TSS generates sample paths at a fraction of the cost of packet-level simulation. Because TSS generates sample paths, it can accurately model state-dependent control mechanisms, including TCP congestion control, adaptive dynamic routing, and so on. We have a TSS implementation for general computer networks with state-dependent control. We have applied this to numerous networks with TCP and state-dependent UDP flows, and confirmed its accuracy against packet-level simulation.