Earticle

Large time delay is one of the key problems of mobile wireless sensor networks, has been working in reducing mobile wireless sensor network data delay has made certain achievements, but for large scale wireless sensor network (WSN) these methods still can not meet the requirements; In addition, there are studies focusing mobile path planning and the ordinary node to node routing separate consideration, without considering gathering node selection, the common node to node routing as well as the relationship between the moving path. Aiming at this problem, and combining the agricultural large scale wireless sensor network, data allow a certain time delay characteristics, on the basis of this scheme, we design a node to node routing heuristic algorithm.

Wireless Sensor Networks (WSNs) have many capabilities like wireless communications, sensing and computation. Due to these advanced features they perform critical tasks in many application areas such as environment monitoring, health applications, rescue operations and many more. One of the major challenges in WSN is efficient data transmission and to achieve this many energy efficient routing protocols have been proposed. Flooding is one of the major communication techniques in this aspect. However it suffers from many problems like implosion, overlap and resource blindness [25]. These problems can be addressed using data-centric data transmission approach. One of the routing protocols employing this approach is Sensor Protocols for Information via Negotiation (SPIN) protocol [2] which uses meta-data to eliminate the transmission of redundant data throughout the network. There are four different SPIN protocols namely SPIN-PP for point to point transmission, SPIN-EC which adds energy conservation heuristic [7], SPIN-BC which is used for broadcast transmission media and SPIN-RL which is a reliable version of SPIN-BC. In this paper a comparative study has been done among flooding and the SPIN protocols.

As more and more non-trivial applications have been deployed in cloud-based systems, the energy consumption of running these applications grow rapidly. Existing studies mainly focus on reducing the CPU-related energy consumption, while ignoring the data-accessing related energy costs. In the paper, we present a novel energy-efficient policy, which is aiming at reducing the data-accessing energy consumption of workflow applications that executed on cloud environments. The proposed policy uses a general energy model to describe the energy consumption of any given workflow. By this application-oriented energy model, a two-phase resource deploying algorithm is implemented, which is capable of generating task scheduling schemes with minimal data-accessing energy consumption. Massive experiments are conducted on a real-world cloud platform, and the results show that the proposed policy outperforms existing approaches in terms of energy efficiency and execution performance.

In large-scale grid systems, plenty of applications are constrained by soft or hard deadline requirement. However, it is difficult to guarantee the deadline requirements of these applications because of the dynamical nature of distributed systems. In this paper, a novel approach is proposed to evaluate the deadline-guarantee of co-allocation schemes that obtained from conventional co-allocation policies. Based on this approach, a hybrid-policy co-allocation model is also proposed to address the issue of deadline-constrained resource co-allocation in grid environments. The proposed model integrates multiple co-allocation policies to generate different co-allocation schemes, and selects the one with optimal deadline-guarantee for grid applications. By this way, the hybrid-policy model combines the merits of different policies, and overcomes the shortcomings of those policies. Extensive simulations are conducted to verify the effectiveness and the performance of the proposed model in terms of deadline-miss rate. Experimental results show that it can provide co-allocation scheme with enhanced deadline-guarantee as well as lower deadline-miss rate.

With increasing demand of new wireless applications and increasing number of wireless user’s problem of spectrum scarcity arises. Cognitive Radio technology supports dynamic spectrum access to address spectrum scarcity problem. Reliability of cognitive operation entirely depends upon how effectively task of spectrum sensing has been performed. Spectrum sensing is a process of discovering voids in spectrum which can be allocated to cognitive users opportunistically. There exists number of traditional spectrum sensing methods in literature for constant noise floor. Practically, noise spectrum density is uncertain under which performance of spectrum sensing scheme degrades. In this paper a new spectrum sensing adaptive algorithm considering noise uncertainty has been proposed. Simulation results of proposed scheme shows a constant detection probability has been achieved under noise uncertainty.

Wireless sensor networks (WSNs) are being envisioned for certain applications like habitat monitoring and environmental sensing. Wireless sensors are deployed to achieve network load balancing, prolonging network lifetime, and improving network coverage. To achieve these goals, energy estimation is one of the main constraints and concerns to consider, while deploying wireless sensors in a WSN field. In this paper, we propose an Energy-efficient based Maximal Lifetime Routing Algorithm to prolong lifetime (EMLRA), which is able to dramatically prolong network lifetime while effectively reducing energy consumption. Through an analytical study, we provide guidance on how to choose parameters in our scheme and demonstrate that the scheme is efficient in both network lifetime and energy consumption. Simulation results show that, with the proposed Energy-efficient based Maximal Lifetime Routing Algorithm in WSN energy consumption, network lifetime, energy consumption balance can be improved in most of cases. It is an available approach to routing decision.

In Ad Hoc network, the randomness of the node’s location makes the network topology highly dynamic change, so it brings great challenges to design and realize the routing algorithm. In this paper, by using the geometry and optimization method to analyze the coverage formed by two and three intersected communication nodes in the Ad Hoc network, we get some important changing relationships about the factors of the node’s distance d and the communication radius r and the coverage area s, and briefly analyze the least number of the communication channels that the other nodes can obtain in the network, and specially discuss the situations of the optimal complete-coverage and its Features. Finally, according to the conclusions, we construct an optimal complete-coverage for a given communication area, and give its logical structure and corresponding formulas calculating the least number of communication nodes. For the researches, it has important significance to design the more efficient routing algorithm and analyze network survivability, and so on.

In Cognitive Radio Networks, selection of primary users (PUs) is an important process for achieving optimal performance during a session. The selection process of PU is limited due to the strict boundaries between layers that are enforced in Open System Interconnection (OSI) model which prevent the coordination, interaction and data transfer between the layers. To overcome such limitations, cross layer optimization is proposed where different operating parameters such as transmission power, packet length, bandwidth etc. across the OSI layers of a device are optimized. In this paper Particle Swarm Optimization (PSO) algorithm is proposed to optimize different operating parameters with the objective to optimize throughput, power consumption, interference, Bit Error Rate and spectral efficiency for a set of PUs across the physical, network and Media Access Control (MAC) layer in OSI model. The fitness values of these objective functions in different modes and channels are investigated using MATLAB and the results shows that PSO is 70% faster than the Genetic Algorithm in terms of convergence rate. Finally paper proposes that PSO based algorithm is an efficient, reliable and fast technique for primary user selection in cognitive radios.

The Cognitive Radio (CR) technology has evolved in the recent past to solve the problem of wireless networks resulting from the limited available spectrum. The networks employing cognitive radios are termed as Cognitive Radio Ad hoc Networks (CRAHN). These networks employ: Primary Users (PUs) and Secondary Users (SUs), PU is the one that have licensed band while the SU uses the licensed band of PU opportunistically for communication purpose. To have communication in CRAHN, a routing protocol is required. The performance of this protocol depends upon various factors such as: mobility, transmission range, number of nodes deployed and environment. This paper is an effort to measure the efficacy of routing protocol by varying the above mentioned factors. For this purpose we implemented a Cognitive Ad hoc On demand Distance Vector (CAODV) routing protocol in MATLAb-09. Moreover, this paper also shows the advantage of CAODV over the standard protocol AODV.

This study focuses on the topics of Quality of Experience which is essentially focused on business users feeling. The purpose of QoE is to realize the user-centered management. QoE is how to come up from the Angle of the user service analyze network service. QoE regards the network service as one unity and considers the various aspects of affecting the network service performance. However by comparison, QoS only pays attention to the network performance which means QoS is one subset of QoE. At present, the difficulty and key point of the study about QoE is how to quickly and effectively compute the indexes which influence QoE. In this paper, in order to solve this problem, we proposed a solution to compute the indexes which influence the QoE result by using the AHP algorithm. And we did an experiment with the real users’ participation in the laboratory which proved that this solution is correct and practicable. It can reflect the QoE result of real end users and provide a valuable reference for the contents provider, ISP and the end service provider about how to provide more stable and higher-quality service.

Future generation optical networks are expected to provide ultra broadband optical communication to continuously growing fiber transmission requirements. In this context, Bismuth and Erbium (Bi/Er) codoped glass fibers symbolize an important aspect as it has offered a promising active laser medium for ultra-bandwidth communication. Many studies have been demonstrated that Bi/Er codoped glass optical fiber showing ultrabroadband luminescence between 1000 and 1570 nm wavelength which typically covering O, E, S, C and L bands of optical window. But, the fluorescence profiles are highly dependent on pump wavelength. This paper provides a survey of the current researches on Bi/Er codoped glass fiber and draws their link to earlier literature on Bi-doped fiber and Er-doped fiber. Also, it present an overview on the key issues that arises during the design of a Bi/Er codoped fiber. Finally, it is intended for a wide range of readers as it covers the topics from basics to advanced aspects.

This paper suggests a cooperative spectrum sensing using dynamic double thresholds energy detection and adaptive grid search to obtain the highest probability detection. The proposed double thresholds are adaptive to noise fluctuation. A new fusion method combined of weighting and voting is used in cooperative sensing. Further, in order to obtain the best sensing performance, we firstly use adaptive grid search to find the optimal double thresholds. Simulation results show that the proposed method has excellent robustness to noise fluctuation and good sensing performance even under low signal to noise ratio (SNR).

Measuring semantic similarity of word pairs is a popular topic for many years. It is crucial in many applications, such as information extraction, semantic annotation, question answering system and so on. It is mandatory to design accurate metric for improving the performance of the bulk of applications relying on it. The paper presents a new metric for measuring word sense similarity using path and information content. Different from previous works, the new metric not only reflects the semantic density information, but also reflects the path information. It is evaluated on the dataset provided by Rubenstein and Goodenough. Experiments demonstrate that the coefficient based on our proposed metric with human judgment is 0.8817, which is significantly outperformed than other existing methods.

In previous B. Steiner channel estimation algorithm adopted in Time Division-Synchronous Code Division Multiple Access (TD-SCDMA) system, but there are some errors in estimated channel due to noise. However, due to using the short training sequences available, the resulting estimation of the channel and detected data suffer from unavoidable errors. In this paper, we analyze the effect of channel estimation error on joint detection and evaluate the performance of TD-SCDMA systems with channel estimation error. The simulation results are consistent with the theory analysis.

In program testing, the accurate information of path feasibility can improve the efficiency of static analysis. The dynamic judgment method of path feasibility needs to execute program, and the resultis usually not sound. On the basis of symbolic execution, this paper proposes a new static judgmentmethod, whichsimultaneouslycomputes two interval sets of each symbolic variable: possible value set and necessary value set. According to these range information, we can easily give the definitejudgment of a path: feasible, infeasible or uncertain. Experiment shows that the method is appropriate and efficient in case of the weakly relevant input.

This paper presents an adjustable sleep scheduling framework for a variety of application in wireless sensor networks (WSNs) so that the lifetime of the network could be prolonged. Varies of typical applications in WSNs are analyzed to identify the same characteristics with which unified interfaces can be designed for all applications, and to identify different characteristics for which interfaces are reserved. This framework can meet the needs of varies applications by simple configuration and adjust itself according to real-time aspects. It can also avoid wasteful duplication, improve work efficiency and provide a good solution to the issue of application independent of sleep scheduling in WSNs. The results of experiments have shown the rationality and practicality of this framework and it can be applied to forest fire monitoring, crop water status monitoring, gas meter reading and other fields.

An aggregate is a digital signature that supports aggregation where any one given n signatures on n distinct messages from n different users can aggregate all these signatures into a single one. We proposed an efficient synchronized aggregate signature scheme from the standard RSA assumption. Our construction is based on the Hohenburger and Waters RSA signature (Crypto 09). This scheme can be proved existentially unforgeable against adaptive chosen-message attacks without random oracles.