854 resultados para software performance evaluation


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Although cooperation generally increases the amount of resources available to a community of nodes, thus improving individual and collective performance, it also allows for the appearance of potential mistreatment problems through the exposition of one node's resources to others. We study such concerns by considering a group of independent, rational, self-aware nodes that cooperate using on-line caching algorithms, where the exposed resource is the storage at each node. Motivated by content networking applications -- including web caching, CDNs, and P2P -- this paper extends our previous work on the on-line version of the problem, which was conducted under a game-theoretic framework, and limited to object replication. We identify and investigate two causes of mistreatment: (1) cache state interactions (due to the cooperative servicing of requests) and (2) the adoption of a common scheme for cache management policies. Using analytic models, numerical solutions of these models, as well as simulation experiments, we show that on-line cooperation schemes using caching are fairly robust to mistreatment caused by state interactions. To appear in a substantial manner, the interaction through the exchange of miss-streams has to be very intense, making it feasible for the mistreated nodes to detect and react to exploitation. This robustness ceases to exist when nodes fetch and store objects in response to remote requests, i.e., when they operate as Level-2 caches (or proxies) for other nodes. Regarding mistreatment due to a common scheme, we show that this can easily take place when the "outlier" characteristics of some of the nodes get overlooked. This finding underscores the importance of allowing cooperative caching nodes the flexibility of choosing from a diverse set of schemes to fit the peculiarities of individual nodes. To that end, we outline an emulation-based framework for the development of mistreatment-resilient distributed selfish caching schemes. Our framework utilizes a simple control-theoretic approach to dynamically parameterize the cache management scheme. We show performance evaluation results that quantify the benefits from instantiating such a framework, which could be substantial under skewed demand profiles.

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Emerging configurable infrastructures such as large-scale overlays and grids, distributed testbeds, and sensor networks comprise diverse sets of available computing resources (e.g., CPU and OS capabilities and memory constraints) and network conditions (e.g., link delay, bandwidth, loss rate, and jitter) whose characteristics are both complex and time-varying. At the same time, distributed applications to be deployed on these infrastructures exhibit increasingly complex constraints and requirements on resources they wish to utilize. Examples include selecting nodes and links to schedule an overlay multicast file transfer across the Grid, or embedding a network experiment with specific resource constraints in a distributed testbed such as PlanetLab. Thus, a common problem facing the efficient deployment of distributed applications on these infrastructures is that of "mapping" application-level requirements onto the network in such a manner that the requirements of the application are realized, assuming that the underlying characteristics of the network are known. We refer to this problem as the network embedding problem. In this paper, we propose a new approach to tackle this combinatorially-hard problem. Thanks to a number of heuristics, our approach greatly improves performance and scalability over previously existing techniques. It does so by pruning large portions of the search space without overlooking any valid embedding. We present a construction that allows a compact representation of candidate embeddings, which is maintained by carefully controlling the order via which candidate mappings are inserted and invalid mappings are removed. We present an implementation of our proposed technique, which we call NETEMBED – a service that identify feasible mappings of a virtual network configuration (the query network) to an existing real infrastructure or testbed (the hosting network). We present results of extensive performance evaluation experiments of NETEMBED using several combinations of real and synthetic network topologies. Our results show that our NETEMBED service is quite effective in identifying one (or all) possible embeddings for quite sizable queries and hosting networks – much larger than what any of the existing techniques or services are able to handle.

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In professional sports there are in general three steps required to improve performance namely task definition, training and performance assessment. This process is iteratively repeated and feedback generated from quantitative performance measurement is in turn used for task redefinition. Task definition can be achieved in a number of ways including via video streaming or indeed and as is more common, by listening to coaching staff. However non-subjective performance evaluation is difficult due to the complexity of the movements involved. When considering the subset of sports where precision accuracy and repeatability are a necessity this problem becomes inherently more difficult to solve. Until recently sports such as martial arts, fencing and darts, where the smallest deviation from a prescribed movement goal can result in large outcome error, were deemed too difficult to characterise fully. Advances in technology, as illustrated by this study, now make this type of physiometry possible.

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The original article is available as an open access file on the Springer website in the following link: http://link.springer.com/article/10.1007/s10639-015-9388-2

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Dense deployment of wireless local area network (WLAN) access points (APs) is an important part of the next generation Wi-Fi and standardization (802.11ax) efforts are underway. Increasing demand for WLAN connectivity motivates such dense deployments, especially in geographical areas with large numbers of users, such as stadiums, large enterprises, multi-tenant buildings, and urban cities. Although densification of WLAN APs guarantees coverage, it is susceptible to increased interference and uncoordinated association of stations (STAs) to APs, which degrade network throughput. Therefore, to improve network throughput, algorithms are proposed in this thesis to optimally coordinate AP associations in the presence of interference. In essence, coordination of APs in dense WLANs (DWLANs) is achieved through coordination of STAs' associations with APs. While existing approaches suggest tuning of APs' beacon powers or using transmit power control (TPC) for association control, here, the signal-to-interference-plus-noise ratio (SINRs) of STAs and the clear channel assessment (CCA) threshold of the 802.11 MAC protocol are employed. The proposed algorithms in this thesis enhance throughput and minimize coverage holes inherent in cell breathing and TPC techniques by not altering the transmit powers of APs, which determine cell coverage. Besides uncoordinated AP associations, unnecessary frequent transmission deferment is envisaged as another problem in DWLANs due to the clear channel assessment aspect of the carrier sensing multiple access collision avoidance (CSMA/CA) scheme in 802.11 standards and the short spatial reuse distance between co-channel APs. To address this problem in addition to AP association coordination, an algorithm is proposed for CCA threshold adjustment in each AP cell, such that CCA threshold used in one cell mitigates transmission deferment in neighboring cells. Performance evaluation reveals that the proposed association optimization algorithms achieve significant gain in throughput when compared with the default strongest signal first (SSF) association scheme in the current 802.11 standard. Also, further gain in throughput is observed when the CCA threshold adjustment is combined with the optimized association. Results show that when STA-AP association is optimized and CCA threshold is adjusted in each cell, throughput improves. Finally, transmission delay and the number of packet re-transmissions due to collision and contention significantly decrease.

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This letter investigates performance enhancement by the concept of multi-carrier index keying in orthogonal frequency division multiplexing (OFDM) systems. For the performance evaluation, a tight closed-form approximation of the bit error rate (BER) is derived introducing the expression for the number of bit errors occurring in both the index domain and the complex domain, in the presence of both imperfect and perfect detection of active multi-carrier indices. The accuracy of the derived BER results for various cases are validated using simulations, which can provide accuracy within 1 dB at favorable channels.

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In this paper, the impact of hardware impairments on secrecy performance of cognitive MIMO schemes is investigated. In addition, the relay which helps the source forward the source signal to the destination can operate either half-duplex mode or full-duplex mode. For performance evaluation, we give the expressions of average secrecy rate over Rayleigh fading channel. Monte-Carlo simulations are presented to compare and optimize the performance of the proposed schemes.

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Multicarrier Index Keying (MCIK) is a recently developed technique that modulates subcarriers but also indices of the subcarriers. In this paper a novel low-complexity detection scheme of subcarrier indices is proposed for an MCIK system and addresses a substantial reduction in complexity over the optimalmaximum likelihood (ML) detection. For the performance evaluation, a closed-form expression for the pairwise error probability (PEP) of an active subcarrier index, and a tight approximation of the average PEP of multiple subcarrier indices are derived in closed-form. The theoretical outcomes are validated usingsimulations, at a difference of less than 0.1dB. Compared to the optimal ML, the proposed detection achieves a substantial reduction in complexity with small loss in error performance (<= 0.6dB).

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This paper presents a thorough performance analysis of dual-hop cognitive amplify-and-forward (AF) relaying networks under spectrum-sharing mechanism over independent non-identically distributed (i.n.i.d.) &#x100000; fading channels. In order to guarantee the quality-of-service (QoS) of primary networks, both maximum tolerable peak interference power Q at the primary users (PUs) and maximum allowable transmit power P at secondary users (SUs) are considered to constrain transmit power at the cognitive transmitters. For integer-valued fading parameters, a closed-form lower bound for the outage probability (OP) of the considered networks is obtained. Moreover, assuming arbitrary-valued fading parameters, the lower bound in integral form for the OP is derived. In order to obtain further insights on the OP performance, asymptotic expressions for the OP at high SNRs are derived, from which the diversity/coding gains and the diversity-multiplexing gain tradeoff (DMT) of the secondary network can be readily deduced. It is shown that the diversity gain and also the DMT are solely determined by the fading parameters of the secondary network whereas the primary network only affects the coding gain. The derived results include several others available in previously published works as special cases, such as those for Nakagami-m fading channels. In addition, performance evaluation results have been obtained by Monte Carlo computer simulations which have verified the accuracy of the theoretical analysis.

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Synchrophasors have become an important part of the modern power system and numerous applications have been developed covering wide-area monitoring, protection and control. Most applications demand continuous transmission of synchrophasor data across large geographical areas and require an efficient communication framework. IEEE C37.118-2 evolved as one of the most successful synchrophasor communication standards and is widely adopted. However, it lacks a predefined security mechanism and is highly vulnerable to cyber attacks. This paper analyzes different types of cyber attacks on IEEE C37.118-2 communication system and evaluates their possible impact on any developed synchrophasor application. Further, the paper also recommends an efficent security mechanism that can provide strong protection against cyber attacks. Although, IEEE C37.118-2 has been widely adopted, there is no clear understanding of the requirements and limitations. To this aim, the paper also presents detailed performance evaluation of IEEE C37.118-2 implementations which could help determine required resources and network characteristics before designing any synchrophasor application.

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We propose a new selective multi-carrier index keying in orthogonal frequency division multiplexing (OFDM) systems that opportunistically modulate both a small subset of sub-carriers and their indices. Particularly, we investigate the performance enhancement in two cases of error propagation sensitive and compromised deviceto-device (D2D) communications. For the performance evaluation, we focus on analyzing the error propagation probability (EPP) introducing the exact and upper bound expressions on the detection error probability, in the presence of both imperfect and perfect detection of active multi-carrier indices. The average EPP results in closedform are generalized for various fading distribution using the moment generating function, and our numerical results clearly show that the proposed approach is desirable for reliable and energy-efficient D2D applications.

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Multi-carrier index keying (MCIK) is a recently developed transmission technique that exploits the sub-carrier indices as an additional degree of freedom for data transmission. This paper investigates the performance of a low complexity detection scheme with diversity reception for MCIK with orthogonal frequency division multiplexing (OFDM). For the performance evaluation, an exact and an approximate closed form expression for the pairwise error probability (PEP) of a greedy detector (GD) with maximal ratio combining (MRC) is derived. The presented results show that the performance of the GD is significantly improved when MRC diversity is employed. The proposed hybrid scheme is found to outperform maximum likelihood (ML) detection with a substantial reduction on the associated computational complexity.