As the rapid growth of open source software, how to choose software from many alternatives becomes a great challenge. Traditional ranking approaches mainly focus on the characteristics of the software themselves, such...
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Determinism is very useful to multithreaded programs in debugging, testing, etc. Many deterministic ap- proaches have been proposed, such as deterministic multithreading （DMT） and deterministic replay. However, thes...
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Determinism is very useful to multithreaded programs in debugging, testing, etc. Many deterministic ap- proaches have been proposed, such as deterministic multithreading （DMT） and deterministic replay. However, these sys- tems either are inefficient or target a single purpose, which is not flexible. In this paper, we propose an efficient and flexible deterministic framework for multithreaded programs. Our framework implements determinism in two steps： relaxed determinism and strong determinism. Relaxed determinism solves data races eificiently by using a proper weak memory consistency model. After that, we implement strong determinism by solving lock contentions deterministically. Since we can apply different approaches for these two steps independently, our framework provides a spectrum of deterministic choices, including nondeterministic system （fast）, weak deterministic system （fast and conditionally deterministic）, DMT system, and deternfinistic replay system. Our evaluation shows that the DMT configuration of this framework could even outperform a state-of-the-art DMT system.
Bloom filters are frequently used to perform set queries that test the existence of some items. However, Bloom filters face a dilemma: the transmission bandwidth and the accuracy cannot be optimized simultaneously. Th...
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This paper investigates the problem of maximizing uniform multicast throughput (MUMT) for multi-channel dense wireless sensor networks, where all nodes locate within one-hop transmission range and can communicate with...
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ISBN:
(纸本)9781509056972
This paper investigates the problem of maximizing uniform multicast throughput (MUMT) for multi-channel dense wireless sensor networks, where all nodes locate within one-hop transmission range and can communicate with each other on multiple orthogonal channels. This kind of networks show wide application in the real world, and maximizing uniform multicast throughput for these networks is worth deep studying. Previous researches have proved MUMT problem is NP-hard. However, previous researches are either hard to implement, or use too many relay nodes to complete the multicast task, and thus incur high overhead or poor performance. To efficiently solve MUMT problem, we adopt the concept of the maximum independent set with the size constraint, and present one novel Single-Broadcast based Multicast algorithm called SBM based on the concept. We prove that SBM algorithm achieves a constant ratio to the theoretical throughput upper bound. Extensive experimental results demonstrate that, SBM performs better than existing work in terms of both the uniform multicast throughput and the total number of transmissions.
Improving the channel utilization is a significant issue to enhance the performance in WLAN. This paper presents, Pillow Talks MAC (PT-MAC), a novel spectrum sharing mechanism to create an extra channel (pt-channel) f...
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Nowadays GPS embedded in mobile device such as smartphones can easily identify people's physical locations. However, in daily life people are more concerned about semantic locations (such as dormitories, laborator...
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ISBN:
(纸本)9781467372121
Nowadays GPS embedded in mobile device such as smartphones can easily identify people's physical locations. However, in daily life people are more concerned about semantic locations (such as dormitories, laboratories, shopping malls, etc.). Usually GPS positioning uses continuous sampling method, which results in a lot of semantically independent sample points. We call these points outliers. How to remove outliers from GPS data and thereby cluster meaningful semantic places is a research challenge in current field of pervasive computing. Aiming at the characteristics of this problem, we first propose a novel approach to add semantic annotations to newly discovered places every day. We use an unsupervised method to discover semantic places, which ensures accuracy of the results and reduces the amount of calculation. Secondly, we discuss the concept of outliers in GPS data collected in daily life, and then eliminate outliers using a density-based method. Moreover, we perform experiments to validate its effectiveness. Thirdly by taking advantage of rule-based inference and reverse geocoding we proposed an approach to calculate the probable semantic labels, which can help user annotate places and reduce the burden on users. Finally, we develop a local System Annotating Semantic Label of Location(SASLL) and by carrying out experiments we demonstrate the validity of our research.
Stragglers can temporize jobs and reduce cluster efficiency *** researches have been contributed to the solution,such as Blacklist[8],speculative execution[1,6],Dolly[8].In this paper,we put forward a new approach for...
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Stragglers can temporize jobs and reduce cluster efficiency *** researches have been contributed to the solution,such as Blacklist[8],speculative execution[1,6],Dolly[8].In this paper,we put forward a new approach for mitigating stragglers in Map Reduce,name *** starts task clones only for high-risk delaying *** experiments have been carried and results show that it can decrease the job delaying risk with fewer resources *** small jobs,Hummer also improves job completion time by 48% and 10% compared to LATE and Dolly.
Multi-NoC (multiple network-on-chip) has demonstrated its advantages in power gating for reducing leakage power. This work presents Chameleon, a novel heterogeneous Multi-NoC design. Chameleon employs a fine-grained p...
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Multi-NoC (multiple network-on-chip) has demonstrated its advantages in power gating for reducing leakage power. This work presents Chameleon, a novel heterogeneous Multi-NoC design. Chameleon employs a fine-grained power gating algorithm which exploits power saving opportunities at different levels of granularity simultaneously. Integrated with a performance-aware traffic allocation policy, Chameleon is able to achieve both high power efficiency and good performance at varying network utilization. Our experimental results show that Chameleon delivers an average of 3.39% higher performance than Catnap, the best in the literature. More importantly, Chameleon consumes an average of 17.16% less power than Catnap.
The coupling of microwaves into apertures plays an important part in many electromagnetic physics and engineering fields. When the width of apertures is very small, Finite Difference Time Domain (FDTD) simulation of t...
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In data center networks, resource allocation based on workload is an effective way to allocate the infrastructure resources to diverse cloud applications and satisfy the quality of service for the users, which refers ...
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In data center networks, resource allocation based on workload is an effective way to allocate the infrastructure resources to diverse cloud applications and satisfy the quality of service for the users, which refers to mapping a large number of workloads provided by cloud users/tenants to substrate network provided by cloud providers. Although the existing heuristic approaches are able to find a feasible solution, the quality of the solution is not guaranteed. Concerning this issue, based on the minimum mapping cost, this paper solves the resource allocation problem by modeling it as a distributed constraint optimization problem. Then an efficient approach is proposed to solve the resource allocation problem, aiming to find a feasible solution and ensuring the optimality of the solution. Finally, theoretical analysis and extensive experiments have demonstrated the effectiveness and efficiency of our proposed approach.
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