Earticle

To become an indispensable part of the Internet of Things (IoT), wireless sensor networks (WSNs) have to be integrated into the Internet. Under such circumstances, any IP-enabled node in the Internet shall be able to directly communicate with any sensor node in a WSN. Then, multiple sensor nodes can be used to monitor an event and jointly generate a report to be sent to one or more Internet nodes for monitoring purposes. Hence, it becomes imperative that every event report that is transmitted from within the WSN be authenticated to intended Internet users and efficiently filtered on its way to the Internet users. However, most present authentication and en-route data filtering schemes developed for WSNs don’t consider the Internet scenario while traditional mechanisms developed for the Internet can hardly be suitable due to resource constraints of sensor nodes in WSNs. In this paper, we propose an authentication and en-route data filtering scheme for WSNs in the IoT scenario in which signature shares based on the most efficient ID-based signature scheme are generated and distributed by making use of verifiable secret sharing cryptography. Security analysis shows that the proposed scheme can defend against node compromise attacks as well as denial of service (DoS) attacks that cause report disruption and selective forwarding problems. Energy consumption as the result of computation and communication is also analyzed to show the advantages of our scheme compared to some other comparable schemes.

Due to the proliferation of low cost wireless sensors, there is growing research interest in their applications, for example, in home healthcare and location tracking. However, due to sensors’ energy resource constraint, some possible applications of sensors have been restricted. In particular, in applications concerning deployment of mobile sensors in dynamic environments, high amounts of energy are consumed by sensors to maintain routing tables. Although existing methods have been proposed to query data from sensors without the use of any routing tables, these methods typically require redundant data to be sent back to the sink and not all of the aggregation functions could be executed precisely. In this paper, we modify an existing method to provide more accurate query answers and extend the lifetime of a wireless sensor network (WSN). According to our simulation, this method outperforms the existing method our approach modifies.

This paper focuses on performance enhancement of large scale of small files transfer, which is critical to the performance of meteorological grid. GridFTP and compression techniques are used to optimize the efficiency. The transfer parameters are configured before transmission, such as extended block mode (Mode E), TCP buffer size. Compression is used to compress files into single file, in order to eliminate negotiating time before transmission. During the course of our research, we sacrifice the disk space for avoiding the vicious recurrence of compression-decompression-compression. In the end, the experiments show the advantages of our approach.

Resource management is traditionally addressed by policies implemented inside the resource provider. Here we study the problem with an attitude that is specular but complementary, which consists in designing a distributed client-side access regulation algorithm that improves the utilization of an elastic resource. The introduction of elastic resources — a feature of the cloud computing paradigm — complicates their management since, when the workload applied on the resource varies (for instance with the number of users) the resource automatically follows such variations with its capacity. But the presence of an extra computational cost related with capacity variations motivates a non linear, lazy response, that penalizes dynamic environments. Hence the interest for an algorithm that shapes the production of service requests on the client side. To make our investigation more adherent to a practical environment, we introduce a real time requirement: each client must have access to the service at least every ꠔ time units. Examples of this requirement, that features a bounded degree of asynchrony, are found, for instance, in network streaming applications: stream chunks must feed the input buffer at the destination. The algorithm we investigate is based on the random walk of a token. To eval- uate the range of applicability of the algorithm, we define an analytic model of its stochastic behavior — described by a non-Markov process — and then we compare its performance with a benchmark algorithm, representative of an effective solution that is often used in practice.

With the development of Wireless Sensor Network (WSN) technology, it has been adopted in a wide variety of applications such as the health care system and so on. Yet, there are still some problems need to be addressed, one of which is the security issue. A lot of schemes from different points of view were proposed to ensure the security in WSNs, however, most of them are proposed for static networks while it is less to consider the situation for the security of the dynamic topology update. Our paper is a novel key management scheme for the dynamic WSNs. The security authentication and random key distribution were initialized in the network deployment phase. During the network stable phase, in order to ensure the real-time update security for the network topology, our scheme proposed a dynamic updated key based on the AVL tree. Simulation result shows that this program can ensure the WSN’s dynamic security as well as achieve the energy efficiency goal.

Cloud computing is becoming an important opportunities for industry to provide a high degree of scalability and serviceability of computing resources. In order to integrate the system resource, utilize the resource flexibly, save the energy consumption, and meet the requirements of users in the cloud computing environment, one of the positive solutions is to apply the virtualization technology. A dynamic resource management with energy saving mechanism has been proposed in this paper which presents a method of dynamic voltage scaling for dynamic adjustment of resources by inspecting CPU utilization in the cloud computing environment. The voltage of the idle or light loaded computer can be reduced and heavy loaded works can be migrated to those machines with lighter loading for achieving the purpose of energy saving. The experimental results show that at the user unaware situation, energy consumption can be saved significantly by applying the proposed mechanism.

Cloud computing provides elastic, scalable on-demand IT services for individuals and organizations. In the cloud computing, everything is as the service. Cloud clients enjoy convenience and efficiency service, but at the same time encounter new issues. Cloud clients needs to provide authentication information to access to service, which often contains a lot of sensitive information. The service provided by Cloud is dynamic, diverse, and context-related. The traditional identity authentication methods which implement coarse-grained to allow or prohibit access is no longer to adapt service-oriented cloud computing. In this paper, we propose a service-oriented identity authentication privacy protection method. In the method, we define cloud service access control as a process and extending the cloud client related information into a fuzzy set as the authentication condition for the exchange, according to the amount of information security level, dynamic opening the corresponding service access control and providing fine-grained service-oriented identity authentication, guarantees global minimal sensitive information disclosure, and maximally protects individual privacy.

Programming models for cloud computing has been a research focus recently. Current programming models for cloud computing mainly focus on improving the efficiency of the cloud computing platforms but little has been done on the performance predictability of models. This paper presents a cloud computing programming model, called BSPCloud. The BSPCloud has the advantages of predictable performance. BSPCloud uses a hybrid of distributed-memory and shared-memory bulk synchronous parallel (BSP) programming model. Computing tasks are first divided into a set of coarse granularity bulks which are computed by the distributed-memory BSP model, and each coarse granularity bulk is further divided into a set of bulk threads which are computed by the shared-memory BSP model. BSPCloud makes full use of the multi-core architecture, and more importantly, the performance of the BSPCloud is predictable. We have implemented a proof-of-concept BSPCloud parallel programming library in java. We give the implementation of BSPCloud parallel programming library and show how the library implements hybrid programming. We detail applying the BSPCloud library on matrix multiplication. The performance predictability and speedup are evaluated in the cloud platform. We give the results of experiments.