8596907
Multiple multicast tree allocation in IP network
The multicasting is defined as the distribution of the same information stream from one to many nodes concurrently. There has been an intensive research effort to design protocols and construct multicast routing graphs for a single multicast group. In this paper, the multiple multicast tree allocation problem is discussed and algorithms are proposed to solve the congestion problem in the IP network. As the congestion measure the minimum residual capacity is considered. Two phase algorithm MMTA is investigated for multiple multicast tree allocation both for identical and different bandwidth requirement by the multicast groups. The central and distributed implementation of the multiple multicast tree is discussed for the deployment in the real IP network. The performance of the proposed MMTA is compared with other procedures. Computational results show that the two-phase MMTA outperforms other procedures. Approximately 3-7% improvement in the residual capacity is obtained by the MMTA. The solution gap from the upper bound by the well-known branch and bound is within 2-11% depending on the problem size.
14489935
Dynamic resource allocation for CDMA-TDD indoor wireless systems
Future wireless communication systems are expected to provide a broad range of multimedia services that have a significant traffic asymmetry between uplink and downlink. The code division multiple access-time division duplex (CDMA-TDD) system is a promising solution to cope with the problem of traffic asymmetry. However, the TDD system is subject to inter-cell interference compared to frequency division duplex (FDD) system. Since both uplink and downlink share the same frequency in TDD, uplink and downlink may interfere each other especially when neighboring cells require different rates of traffic load. Thus, the resource allocation among cells is an important issue in TDD. In this paper, the resource allocation in the CDMA-TDD is formulated as a mixed integer programming (MIP) problem. A dynamic resource allocation algorithm (DRAA) is provided that effectively solves the traffic asymmetry problem. The MIP problem is also solved by a well-known branch and bound procedure. Both the crossed slot and non-crossed slot allocation are examined and compared to the DRAA. Computational result shows that proposed DRAA gives a good performance as the traffic asymmetry increases between the uplink and downlink. Copyright Â© 2003 John Wiley & Sons, Ltd.
32212919
Balancing loads on sonet rings with integer demand splitting
SONET Self Healing ring is one of the most intriguing schemes which provide survivability for telecommunication networks. To design a cost effective SONET ring it is necessary to consider load balancing problems by which the link capacity is determined. In this paper, we consider the load balancing problem in SONET ring when demand splitting is allowed only by integer. A bounded approximation to the optimal solution is presented and proved by employing the arc-demand matrix which represents the amount of demand routed on each arc. A very efficient algorithm is provided which always satisfies the optimality at termination. The algorithm iteratively decreases the maximum load by considering counter-clockwise routing of a demand which passes through the arc with maximum load. Justification of the algorithm is also provided.
13953434
A design of multi‐layered location registration areas in microcellular systems
Multi‐layered location registration areas are considered to minimize the control signals at boundary cells in the microcellular systems. The decision of multi‐layered location registration (LR) areas is formulated as an integer programming problem by examining the regional subscriber densities, traffic flows and call arrival rates. By relaxing the constraints of forward and reverse control channels the problem is decomposed into a number of subproblems each of which corresponds to a layer. Each subproblem is solved via a modified graph partitioning algorithm. Feasible LR areas are obtained by considering the two relaxed constraints. Computational experiments are performed in a system with 80 microcells to investigate the performance of the proposed multi‐layer scheme. The simulation results indicate that the two‐layer scheme generally outperforms the one‐layer and three‐layer methods in view of control signals.
9335901
Performance upgrade for large object bases using disk arrays
The authors propose the use of multiple disks to increase the bandwidth of disk I/O so as to alleviate the I/O bottleneck problem existed in OODB applications. However, a major difficulty in using multiple disks for the support of OODBs is that an object may reference or be referenced by other objects through associations. This requires that the search of objects be sequential through the association links, which is sometimes referred to as the navigational search of objects in an object base. This restriction limits the concurrency in object retrieval and invalidates the use of multiple disks. Techniques such as clustering/indexing of objects do not help to resolve this problem. By using a two-phase query processing strategy previously proposed by them, objects of interest can be accessed in parallel from multiple disk. The aim of the paper is to design a probability-based evaluation model to estimate the performance of using multiple disks and to compare it with a single disk system. The result shows that the scheme is viable and a significant improvement is achieved while multiple disks are used.
9259468
Classification of Multiple Cancer Types by Multicategory Support Vector Machines Using Gene Expression Data
MOTIVATION
High-density DNA microarray measures the activities of several thousand genes simultaneously and the gene expression profiles have been used for the cancer classification recently. This new approach promises to give better therapeutic measurements to cancer patients by diagnosing cancer types with improved accuracy. The Support Vector Machine (SVM) is one of the classification methods successfully applied to the cancer diagnosis problems. However, its optimal extension to more than two classes was not obvious, which might impose limitations in its application to multiple tumor types. We briefly introduce the Multicategory SVM, which is a recently proposed extension of the binary SVM, and apply it to multiclass cancer diagnosis problems.


RESULTS
Its applicability is demonstrated on the leukemia data (Golub et al., 1999) and the small round blue cell tumors of childhood data (Khan et al., 2001). Comparable classification accuracy shown in the applications and its flexibility render the MSVM a viable alternative to other classification methods.


SUPPLEMENTARY INFORMATION
http://www.stat.ohio-state.edu/~yklee/msvm.htm
11513651
A scalable solution to the multi-resource QoS problem
The problem of maximizing system utility by allocating a single finite resource to satisfy discrete Quality of Service (QoS) requirements of multiple applications along multiple QoS dimensions was studied previously. In this paper we consider the more complex problem of apportioning multiple finite resources to satisfy the QoS needs of multiple applications along multiple QoS dimensions. In other words, each application, such as video-conferencing, needs multiple resources to satisfy its QoS requirements. We evaluate and compare three strategies to solve this provably NP-hard problem. We show that dynamic programming and mixed integer programming compute optimal solutions to this problem but exhibit very long running times. We then adapt the mixed integer programming problem to yield near-optimal results with smaller running times. Finally, we present an approximation algorithm based on a local search technique that is less than 5% away from the optimal solution but which is more than two orders of magnitude faster. Perhaps more significantly, the local search technique turns out to be very scalable and robust as the number of resources required by each application increases.
2900634
Radar dwell scheduling considering physical characteristics of phased array antenna
This paper proposes novel techniques for scheduling radar dwells in phased array radar systems. In order to handle complex physical characteristics such as dwell interleaving, transmitting duty cycle constraint, and energy constraint, we propose a notion of schedulability envelope. The schedulability envelope designed offline hides the details of complex radar dwell scheduling and provides a simple measure for the schedulability check. Using the schedulability envelope, the proposed technique can efficiently perform the admission control for dynamic target tracking tasks. The simulation results show that the proposed approach can significantly improve the system utilization by taking advantage of dwell interleaving while guaranteeing the schedulability and physical constraints.
7460330
Enhanced analysis of cache-related preemption delay in fixed-priority preemptive scheduling
We propose an enhanced technique for analyzing, and thus bounding cache related preemption delay in fixed priority preemptive scheduling focusing on instruction caching. The proposed technique improves upon previous techniques in two important ways. First, the technique takes into account the relationship between a preempted task and the set of tasks that execute during the preemption when calculating the cache related preemption delay. Second, the technique considers phasing of tasks to eliminate many infeasible task interactions. These two features are expressed as constraints of a linear programming problem whose solution gives a guaranteed upper bound on the cache related preemption delay. The paper also compares the proposed technique with previous techniques. The results show that the proposed technique gives up to 60% tighter prediction of the worst case response time than the previous techniques.