In multi-target tracking, a data association hypothesis assigns measurements to tracks, and the hypothesis likelihood (of the joint target-measurement associations) is used to compare among all hypotheses for truncati...
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ISBN:
(纸本)9781665414272
In multi-target tracking, a data association hypothesis assigns measurements to tracks, and the hypothesis likelihood (of the joint target-measurement associations) is used to compare among all hypotheses for truncation under a finite compute budget. It is often assumed however that an individual target-measurement association likelihood is independent of others, i.e., it remains the same in whichever hypothesis it belongs to. In the case of Track Oriented Multiple Hypothesis Tracking (TO-MHT), this leads to a parsimonious representation of the hypothesis space, with a maximum a posteriori solution obtained through solving an integer linear programming problem. In Labeled Random Finite Set (Labeled RFS) filters, this leads to an efficient way of obtaining the top ranked hypotheses through solving a ranked assignment problem using Murty’s algorithm. In this paper we present a Propose and Verify approach for certain Dependent Likelihood Structures, such that the true hypothesis likelihood is evaluated jointly for the constituent track-measurement associations to account for dependence among them, but at the same time that ranking is still obtained efficiently. This is achieved by proposing a candidate ranking under an assumption of independence, and then evaluating the true likelihood one by one, which is guaranteed, for certain Dependent Likelihood Structures, to not increase from its candidate value, until the desired number of top ranked hypotheses are obtained. Examples of such Dependent Likelihood Structures include the Collision Likelihood Structure and the Occlusion Likelihood Structure, both encountered frequently in applications.
We discover significant value-dependent programming energy variations in multi-level cell (MLC) flash memories, and introduce an energy-aware data compression method that minimizes the flash programming energy rather ...
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ISBN:
(纸本)9781595936271
We discover significant value-dependent programming energy variations in multi-level cell (MLC) flash memories, and introduce an energy-aware data compression method that minimizes the flash programming energy rather than the size of the compressed data. We express energy-aware data compression as an entropy coding with unequal bit-pattern costs. Deploying a probabilistic approach, we derive the energy-optimal bit-pattern probabilities and the expected values of the bit-pattern costs for the large amounts of compressed data which are typical in multimedia applications. Then we develop an energy-optimal prefix coding that uses integer linear programming, and construct a prefix code table. From a consideration of Pareto-optimal energy consumption, we make tradeoffs between data size and programming energy, such as a 35% energy saving for a 50% area overhead.
The Future Internet demands energy efficient communication to cope with the ever increasing power consumption. Virtualization techniques have proved to be effective in reducing power consumption of network devices. An...
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ISBN:
(纸本)9781457720529
The Future Internet demands energy efficient communication to cope with the ever increasing power consumption. Virtualization techniques have proved to be effective in reducing power consumption of network devices. An open issue in virtualization for green networking is the search for an energy-efficient mapping of virtual networks onto physical networks. This paper introduces a new model for the mapping of virtual networks which aims at reducing the energy consumption. This model is based on an integer linear programming formulation and several parameters, corresponding to characteristic of real networks, are considered. Simulation results attest the efficacy of the proposal.
The vision for economies of reusable services that can be composed into business processes is still hindered by the lack of dependability as regards their execution. Service Level Agreements (SLAs) are an instrument t...
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ISBN:
(纸本)9781424467280;9780769540221
The vision for economies of reusable services that can be composed into business processes is still hindered by the lack of dependability as regards their execution. Service Level Agreements (SLAs) are an instrument to express and codify requirements for services, so that an acceptable level of determinism can be provided, and customers can rely on them as such. In this work we present the SLA Management Instance (SAMI) architecture for a reusable autonomic entity that can support negotiation and runtime management of SLAs, without disruptive effects on the existing corresponding services. This architecture takes extra steps towards supporting hierarchies of cross-domain SLAs, reflecting similar hierarchies of cross-domain service compositions.
Schedulability analysis of real-time embedded systems requires worst case timing guarantees of embedded software performance. This involves not only language level program analysis, but also modeling the effects of co...
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ISBN:
(纸本)9781581136883
Schedulability analysis of real-time embedded systems requires worst case timing guarantees of embedded software performance. This involves not only language level program analysis, but also modeling the effects of complex micro-architectural features in modern processors. Speculative execution and caching are very common in current processors. Hence one needs to model the effects of these features on the Worst Case Execution (WCET) of a program. Even though the individual effects of these features have been studied recently, their combined effects have not been investigated. We do so in this paper. This is a non-trivial task because speculative execution can indirectly affect cache performance (e.g., speculatively executed blocks can cause additional cache misses). Our technique starts from the control flow graph of the embedded program, and uses integer linear programming to estimate the program's WCET. The accuracy of our modeling is illustrated by tight estimates obtained on realistic benchmarks.
Estimating the worst case execution time (WCET) of a program on a given processor is important for the schedulability analysis of real-time systems. WCET analysis techniques typically model the timing effects of micro...
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Estimating the worst case execution time (WCET) of a program on a given processor is important for the schedulability analysis of real-time systems. WCET analysis techniques typically model the timing effects of microarchitectural features in modern processors (such as the pipeline, caches, branch prediction, etc.) to obtain safe but tight estimates. In this paper, we model out-of-order processor pipelines for WCET analysis. This analysis is, in general, difficult even for a basic block (a sequence of instructions with single-entry and single-exit points) if some of the instructions have variable latencies. This is because the WCET of a basic block on out-of-order pipelines cannot be obtained by assuming maximum latencies of the individual instructions. Our timing estimation technique for a basic block is inspired by an existing performance analysis technique for tasks with data dependencies and resource contentions in real-time distributed systems. We extend our analysis by modeling the interaction among consecutive basic blocks as well as the effect of instruction cache. Finally, we employ integer linear programming (ILP) to compute the WCET of an entire program. The accuracy of our analysis is demonstrated via tight estimates obtained for several benchmarks.
A two-layer transportation network design model with three objectives is introduced. The objectives are: the minimization of the primary path length (or traveling time) from a predetermined starting node to a predeter...
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A two-layer transportation network design model with three objectives is introduced. The objectives are: the minimization of the primary path length (or traveling time) from a predetermined starting node to a predetermined terminus node; the minimization of the total distance traversed by the demand to reach a node on the primary path; and the minimization of the total network construction cost. The problem is initially formulated as an integer linear programming model. A combinatoric solution which would be suitable for small networks because of the large size of the subtour breaking constraints is presented. The method produces efficient solutions according to the objectives mentioned above. The criteria of alternate transportation facilities, environmental concerns, and socio-economic structure are included for these efficient solutions. By using Zeleny's ideal point approach the best compromise solution is then selected. The results of a numerical example are also given. Some potential applications of the model include the planning of a new highway or rapid transportation system and the design of an energy distribution system.< >
This paper provides a suite of approaches to solving the survivable routing problem with shared protection. The problem diverse solving the least-cost working and protection path-pair (in terms of the sum of the cost)...
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This paper provides a suite of approaches to solving the survivable routing problem with shared protection. The problem diverse solving the least-cost working and protection path-pair (in terms of the sum of the cost) is formulated into integer linear programming. We also introduce two heuristic algorithms, called iterative two-step-approach (ITSA) and maximum likelihood relaxation (MLR), which aim to finding the approximating optimal solution within a limited amount of computation time. We examine the performance of the proposed schemes and make a comparison with some reported counterparts. It is observed that the ITSA scheme with a properly defined tolerance to the optimality can achieve the best performance at the expense of much longer computation time. MLR can provide an ultra-fast path selection process, which behaves as a good tradeoff between computation efficiency and performance.
This paper introduces an integrated approach for the recovery of a timetable by rescheduling train services and rolling stock circulation with the reassignment of disrupted passengers who are supposed to travel on the...
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ISBN:
(数字)9781728141497
ISBN:
(纸本)9781728141503
This paper introduces an integrated approach for the recovery of a timetable by rescheduling train services and rolling stock circulation with the reassignment of disrupted passengers who are supposed to travel on the train service cancelled due to the broken rolling stock in a railway transportation system with the seat-reserved mechanism. We propose a novel integer linear programming model to maximize the number of disrupted passengers arriving at their pre-planned destinations, and to minimize the total delay of all train services and the number of cancelled train services. The mathematical formulation deals with the reassignment of disrupted passengers to non-cancelled train services by planning extra stops and the reassignment of rolling stocks to train services with consideration of the maintenance distance, limited seat capacity and required turnaround time. Other constraints focus on the limited track capacity, extra running time of deceleration and acceleration due to extra stops, and mapping the timetable rescheduling, the assignment of rolling stock and passengers. Numerical experiments based on a part of the Beijing-Shanghai high-speed railway line are carried out to verify the effectiveness and efficiency of the proposed method.
In this work, we study the problem of efficient service provisioning in light-trail WDM optical networks under a scheduled traffic model. In this model, a set of demands is given, and the setup time, teardown time, an...
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ISBN:
(纸本)9781424414321
In this work, we study the problem of efficient service provisioning in light-trail WDM optical networks under a scheduled traffic model. In this model, a set of demands is given, and the setup time, teardown time, and the requested bandwidth of a demand are known in advance. When constructing light-trails to accommodate scheduled demands, we consider two cases: static light-trail case and dynamic light-trail case. In the static light-trail case, a light-trail will not be torn down once it is set up. In the dynamic light-trail case, a light-trail can be torn down when it is not used by any scheduled demand, so that the resources for that light-trail can be re-allocated for other light-trails. We present integer linear programming (ILP) formulations for this problem while considering the instantiation of static light-trails as well as dynamic light-trails to provision scheduled services. The optimization objective is to minimize the resources used in terms of the total wavelength-links used to accommodate a set of demands. Time efficient heuristic algorithms are then proposed for both cases. The solutions to the ILP formulations and the extensive simulation of the heuristic algorithms show that the use of dynamic light-trails significantly reduces the required resources to accommodate the same demand set. The resource reduction becomes more significant as the size of demand sets increases and the time correlation among demands becomes weaker. The heuristic algorithms for both cases are also shown to be very time efficient.
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