Weigh-in-motion (WIM) is a better way that can gain the true weight of vehicle which is moving on the highway at a high speed. In this paper, the principle of piezoelectric sensor is introduced, and the WIM signal mod...
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In a chip-multiprocessor with a shared cache structure, the last level cache is shared by multiple applications executing simultaneously. the competing accesses from different applications degrade the system performan...
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ISBN:
(纸本)9781424449903
In a chip-multiprocessor with a shared cache structure, the last level cache is shared by multiple applications executing simultaneously. the competing accesses from different applications degrade the system performance, resulting in non-predicting executing time. Cache partitioning techniques partition the shared cache for multiple applications. Traditional cache partitioning mechanisms such as Utility-based Cache Partitioning (UCP) and IPC-based Cache Partitioning (IPC-CP), aim to optimize the objective (for example, instruction per cycle or miss rate) that is appealing for individual application. However, the performances of multi-programmed systems are usually characterized by the number of applications finished during certain interval. this paper investigates System Level Speedup oriented Cache Partitioning (SLS-CP), which is used to maximize total speedup of the system. Like UCP and IPC-CP, the inputs of SLS-CP are current performance status and misses of all the possible partitions, and the outputs of SLS-CP are optimum cache partitions for multiprogrammed workloads. Our evaluation, on top of a two cores CMP processor with 8 multi-programmed workloads shows that SLS-CP improves system level speedup and fairness over UP and IPC-CP.
Large-scale autonomic systems are required to self-optimize with respect to high-level policies, that can differ in terms of their priority, as well as their spatial and temporal scope. Decentralized multi-agent syste...
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ISBN:
(纸本)9783642027031
Large-scale autonomic systems are required to self-optimize with respect to high-level policies, that can differ in terms of their priority, as well as their spatial and temporal scope. Decentralized multi-agent systems represent one approach to implementing the required self-optimization capabilities. However, the presence of multiple heterogeneous policies leads to heterogeneity of the agents that implement them. In this paper we evaluate the use of Reinforcement Learning techniques to support the self-optimization of heterogeneous agents towards multiple policies in decentralized systems. We evaluate these techniques in an Urban Traffic Control simulation and compare two approaches to supporting multiple policies. Our results suggest that approaches based on W-learning, which learn separately for each policy and then select between nominated actions based on current action importance, perform better than combining policies into a single learning process over a single state space. the results also indicate that explicitly supporting multiple policies simultaneously can improve waiting times over policies dedicated to optimizing for a single vehicle type.
In this paper, we study the code distribution problem in multi-application wireless sensor networks (MA-WSNs), i.e., sensor networks that can support multiple applications. While MA-WSNs have many advantages over trad...
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ISBN:
(纸本)9783642020841
In this paper, we study the code distribution problem in multi-application wireless sensor networks (MA-WSNs), i.e., sensor networks that can support multiple applications. While MA-WSNs have many advantages over traditional WSNs, they tend to require frequent code movements in the network, and thus here new challenges for designing energy efficient code dissemination protocols. We propose MCP, a stateful Multicast based Code redistribution Protocol for achieving energy efficiency. Each node in MCP maintains a small table to record the interesting information of known applications. the table enables sending out multicast-based code dissemination requests such that only a subset of neighboring sensors contribute to code dissemination. Compared to broadcasting based schemes, MCP greatly reduces signal collision and saves boththe dissemination time and reduces the number of dissemination messages. Our experiments results show that MCP can reduce dissemination time by 25% and message overhead by 20% under various network settings.
Wireless Mesh Network (WMN) is an emerging communication paradigm to enable resilient, cost-efficient and reliable services for the future-generation wireless networks. In this paper, we study the problem of multipoin...
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ISBN:
(纸本)9781424451142
Wireless Mesh Network (WMN) is an emerging communication paradigm to enable resilient, cost-efficient and reliable services for the future-generation wireless networks. In this paper, we study the problem of multipoint-to-multipoint (M2M) multicasting in a WMN which aims to use the minimum number of time slots to exchange messages among a group of k mesh nodes in a multi-hop WMN with n mesh nodes. We study the M2M multicasting problem in a distributed environment where each participant only knows that there are k participants and it does not know who are other k - 1 participants among n mesh nodes. It is known that the computation of an optimal M2M multicasting schedule is NP-hard. We present a fully distributed deterministic algorithm for such an M2M multicasting problem and analyze its time complexity. We show that if the maximum hop distance between any two out of the k participants is d, then the studied M2M multicasting problem can be solved in time O(d log(2) n + k log(3) n/log k) with a polynomial-time computation, which is an almost optimal scheme due to the lower bound Omega(d + k log n/log k) given in [5]. Our algorithm also improves the currently test known result with running time O(d log(2) n + k log(4) n) in [13]. In this paper, we also propose a distributed deterministic algorithm which accomplishes the M2M multicasting in time O(d + k) with a polynomial-time computation in unit disk graphs. this is an asymptotically optimal algorithm in the sense that there exists a WMN topology, e.g., a line, a ring, a star or a complete graph, in which the M2M multicasting cannot be completed in less than Omega(d + k) units of time.
this paper establishes a distributed and coordinated traffic signal control system based on multi-agent (DTCMAS), in which there is no control center. Each intersection is controlled by a local agent independently. In...
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Internet of things technologies makes it possible to trace when and where the excellent food or wine is spoiled or loses perfect taste in logistics and retail. this paper describes a system using a two-layered wireles...
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Data fusion or In-network processing methods were often adopted in Wireless sensor Networks (WSNs) to reduce data communication and prolong network lifetime, which made WSNs application can be described as a set of ta...
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ISBN:
(纸本)9789639799592
Data fusion or In-network processing methods were often adopted in Wireless sensor Networks (WSNs) to reduce data communication and prolong network lifetime, which made WSNs application can be described as a set of tasks (sensing, processing) and dependencies among them. Task assignment has become an important problem which needed to be resolved for different tasks assignment caused different energy consumption. Based on the task graph of WSNs, an energy-efficient task assignment framework was proposed. As application task can be decomposed into sensing subtasks and processing subtasks, we present the task assignment as sensing subtask assignment and processing subtask assignment. We formulate the processing subtask assignment as a 0-1 quadratic programming problem and evaluate it through experiments.
Existing huge E-Commerce web sites such as Amazon and eBay tends to have a recommendation function to stimulate customer's potential needs by analyzing their click information. On the other hand, POS (Point of sal...
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Geographic forwarding is a favorable scheme for data reporting in Wireless sensor Networks (WSNs) due to its simplicity and low-overhead. However, WSNs are usually subject to complicated environmental factors. Network...
ISBN:
(纸本)9781424451142
Geographic forwarding is a favorable scheme for data reporting in Wireless sensor Networks (WSNs) due to its simplicity and low-overhead. However, WSNs are usually subject to complicated environmental factors. Network holes (i.e., the areas where no nodes inside) and barriers (i.e., those blocking the communication between two close nodes) are inevitable in practical deploying environments. these issues pose an obstacle to adopting geographic forwarding in WSNs, while current approaches lack an efficient method to tolerate such negative factors. In this paper we specifically tailor a waypoint-based Geographic Data Reporting Protocol (GDRP) for WSNs. Inherited from geographic forwarding, GDRP is light-weighted and hence well-suits WSNs. But unlike current approaches that often find suboptimal paths, GDRP adopts an intelligent strategy to select a best set of waypoints via which packets can efficiently circumvent holes and barriers, and it can thus find better paths. Extensive simulations are conducted to verify the advantages of GDRP in tolerating network holes and obstacles in WSNs.
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