32342128
Performance Analysis of an Input Queueing ATM Switch with Two Priority Classes
Abstract In this paper, we study an input queueing asynchronous transfer mode (ATM) switch with the preemptive priority scheme. Up to now, many researchers have studied this switch, but their models do not yield accurate results. Therefore, we propose another model and analyze the performance of the switch for two different arrival processes, that is, the independent priority arrival process (IPAP) and the dependent priority arrival process (DPAP). In this paper, we model a virtual head of line (HOL) queue like the previous works, and analyze it using a three-dimensional Markov chain. As for each input queue, we model it as a two-class Geomx/Geom/1 queue with preemptive priority. By using this model, we obtain the mean queueing delay of the low priority class and the maximum throughput of the switch. In case of the IPAP, we compare our result with simulation and those of the previous works to show that our model yields more accurate results. In addition, we compare the performances of those two arrival processes to illustrate their difference.
11623554
Downlink power allocation for multi-class CDMA wireless networks
We use a utility based power allocation framework in the downlink to treat multi-class CDMA wireless services in a unified way. Our goal is to obtain a power allocation which maximizes the total system utility. Natural utility functions for each mobile are non-concave. Hence we cannot use existing techniques on convex optimization problems to derive a social optimal solution. We propose a simple distributed algorithm to obtain an approximation to the social optimal power allocation. The algorithm is based on dynamic pricing and allows partial cooperation between mobiles and the base station. The algorithm consists of two stages. At the first stage, the base station selects mobiles to which power is allocated, considering their partial-cooperative nature. This is called partial-cooperative optimal selection, since in a partial-cooperative setting and pricing scheme, this selection is optimal and satisfies system feasibility. At the next stage, the base station allocates power to the selected mobiles. This power allocation is a social optimal power allocation among mobiles in the partial-cooperative optimal selection, thus, we call it a partial-cooperative optimal power allocation. We compare the partial-cooperative optimal power allocation with the social optimal power allocation for the single class case. From these results, we infer that the system utility obtained by partial-cooperative optimal power allocation is quite close to the system utility obtained by social optimal allocation.
7032611
Utility-Optimal Medium Access Control: Reverse and Forward Engineering
This paper analyzes and designs medium access control (MAC) protocols for wireless ad-hoc networks through the network utility maximization (NUM) framework. We first reverse-engineer the current exponential backoff (EB) type of MAC protocols such as the BEB (binary exponential backoff) in the IEEE 802.11 standard through a non-cooperative game- theoretic model. This MAC protocol is shown to be implicitly maximizing, using a stochastic subgradient, a selfish local utility at each link in the form of expected net reward for successful transmission. While the existence of a Nash equilibrium can be established, neither convergence nor social welfare optimality is guaranteed due to the inadequate feedback mechanism in the EB protocol. This motivates the forward-engineering part of the paper, where a network-wide utility maximization problem is for- mulated, using a collision and persistence probability model and aligning selfish utility with total social welfare. By adjusting the parameters in the utility objective functions of the NUM problem, we can also control the tradeoff between efficiency and fairness of radio resource allocation through a rigorous and systematic design. We develop two distributed algorithms to solve the MAC design NUM problem, which lead to random access protocols that have slightly more message passing overhead than the current EB protocol, but significant potential for efficiency and fairness improvement. We provide readily-verifiable sufficient conditions under which convergence of the proposed algorithms to a global optimality of network utility can be guaranteed, and through numerical examples illustrate the value of the NUM approach to the complexity-performance tradeoff in MAC design.
16485757
Reverse Engineering MAC
This paper reverse engineers backoff-based random-access MAC protocols in ad-hoc networks. We show that the contention resolution algorithm in such protocols is implicitly participating in a non-cooperative game. Each link attempts to maximize a selfish local utility function, whose exact shape is reverse engineered from the protocol description, through a stochastic subgradient method in which the link updates its persistence probability based on its transmission success or failure. We prove that existence of a Nash equilibrium is guaranteed in general. The minimum amount of backoff aggressiveness needed for uniqueness of Nash equilibrium and convergence of the best response strategy are established as a function of user density. Convergence properties and connection with the best response strategy are also proved for variants of the stochastic-subgradient-based dynamics of the game. Together with known results in reverse engineering TCP and BGP, this paper completes the recent efforts in reverse engineering the main protocols in layers 2-4.
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.
20717190
Opportunistic power scheduling for multi-server wireless systems with minimum performance constraints
We present and power scheduling scheme, i.e., a joint time-slot and power allocation method for wireless cellular systems. We allow multiple transmissions in a time-slot that can interfere with each other. Hence, it is important to not only select the mobiles to he scheduled in a time-slot, hut also important to allocate an appropriate power level for transmission to these scheduled mobiles in order to achieve high system performance and quality of service. We model the time-varying wireless channel as a stochastic process and formulate a stochastic programming problem that attempts to maximize the expected total system utility, with constraints on the minimum expected utility for each mobile. The power scheduling algorithm is obtained by using stochastic duality and implemented via stochastic subgradient techniques.
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.
3952650
Haptic pen: a tactile feedback stylus for touch screens
In this paper we present a system for providing tactile feedback for stylus-based touch-screen displays. The Haptic Pen is a simple low-cost device that provides individualized tactile feedback for multiple simultaneous users and can operate on large touch screens as well as ordinary surfaces. A pressure-sensitive stylus is combined with a small solenoid to generate a wide range of tactile sensations. The physical sensations generated by the Haptic pen can be used to enhance our existing interaction with graphical user interfaces as well as to help make modern computing systems more accessible to those with visual or motor impairments.
14431473
Two-Phase Barrier: A Synchronization Primitive for Improving the Processor Utilization
Barrier is widely used for synchronization in parallel programs. Since the process arrived earlier than others should wait at the barrier, the total processor utilization decreases. In this paper, to find the sources of the barrier waiting time, parallel programs are executed on the various grain sizes through execution-driven simulations. In simulation studies, we found that even if approximately equal amounts of work are distributed to each processor, all processes may not arrive at a barrier at the same time. The reasons are that the different numbers of cache misses and instructions within in partitioned grains result in the difference in arrival time of processors at the barrier. In this paper, the two-phased barrier is considered to reduce the blind waiting time in the traditional barrier scheme, which can be simply constructed by dividing one specific stage for the synchronization into two stages. On each stage, processes decide their stall or not, which is dependent on the current execution state of grains running on any given processors. Simulation results show that the reduced barrier waiting times attributed to the two-phased barrier contribute to the performance improvement of parallel programs.
7460855
Automatic Code Mapping on an Intelligent Memory Architecture
This paper presents an algorithm to automatically map code on a generic intelligent memory system that consists of a high-end host processor and a simpler memory processor. To achieve high performance with this type of architecture, the code needs to be partitioned and scheduled such that each section is assigned to the processor on which it runs most efficiently. In addition, the two processors should overlap their execution as much as possible. With our algorithm, applications are mapped fully automatically using both static and dynamic information. Using a set of standard applications and a simulated architecture, we obtain average speedups of 1.7 for numerical applications and 1.2 for nonnumerical applications over a single host with plain memory. The speedups are very close and often higher than ideal speedups on a more expensive multiprocessor system composed of two identical host processors. Our work shows that heterogeneity can be cost-effectively exploited and represents one step toward effectively mapping code on heterogeneous intelligent memory systems.
11330211
Resolving References to Graphical Objects in Multimodal Queries by Constraint Satisfaction
In natural language queries to an intelligent multimodal system, ambiguities related to referring expressions - source ambiguities - can occur between items in the visual display and objects in the domain being represented. A multimodal interface has to be able to resolve these ambiguities in order to provide satisfactory communication with a user. In this paper, we briefly introduce source ambiguities, and present the formalisation of a constraint satisfaction approach to interpreting singular referring expressions with source ambiguities. In our approach, source ambiguities are resolved simultaneously with other referent ambiguities, allowing flexible access to various sorts of knowledge.