Springer Science and Business Media LLC

Silver Beach is a typical sandy plain coast located in the southeastern city of Beihai in Guangxi province, China. Because of its obvious land-use changes and ecosystem deterioration in recent decades, a sustainable development management and environmental protection project should be urgently proposed. Therefore, the remote-sensing images of Landsat are adopted to analyze the land use evolution and to evaluate its ecological security during the past 35 years in Silver Beach of this paper. The results show: in the period of 1979a–2013a, the areas of constructive land and artificial wetland are considerably increased and mainly transformed from cultivated land and forest land. The areas of cultivated land and forest land are substantially reduced accordingly, but the areas of grassland, water area and intertidal zone have no great extent of variation. Its land use intensities are consistently increased, but its land use diversities are abundant before 2000a and then significant decreased. Overall, the land use evolution presents slow in development speed, strengthen in development intensity, down in ecological richness and fragment in spatial patterns. In terms of ecological security, although there has short-term rising of ecological service value and security in 2006a, the whole structure, stability and ecological service function in Silver Beach are declined, and its vulnerabilities are accordingly increased. As a matter of fact, these results are achieved by shortly to improve the utilization rate of the artificial wetland and the intertidal zone resources with the cost of ecosystem structure and stability destruction. The impact factors of leading to above results are not only climatic factors as air temperature, typhoon, tide, but also even more important human activity factors as urbanization, sea reclamation, fishing, tourism and planning management in the studied time period. In consequence, the research findings from this study should be able to help understand the interacting mechanism among above multiple factors and to quantify respective contribution to land use evolution and its ecological security, which would provide an importantly scientific instruction for the future development management protection in Silver Beach.

Artificial Bee Colony (ABC) algorithm is a nature-inspired algorithm that showed its efficiency for optimizations. However, the ABC algorithm showed some imbalances between exploration and exploitation. In order to improve the exploitation and enhance the convergence speed, a multi-population ABC algorithm based on global and local optimum (namely MPGABC) is proposed in this paper. First, in MPGABC, the initial population is generated using both chaotic systems and opposition-based learning methods. The colony in MPGABC is divided into several sub-populations to increase diversity. Moreover, the solution search mechanism is modified by introducing global and local optima in the solution search equations of both employed and onlookers. The scout bees in the proposed algorithm are generated similarly to the initial population. Finally, the proposed algorithm is compared with several state-of-art ABC algorithm variants on a set of 13 classical benchmark functions. The experimental results show that MPGABC competes and outperforms other ABC algorithm variants.

Cloud computing is an important technology for businesses and individual users to obtain computing resources over the Internet on-demand and flexibly. Although cloud computing has been adopted across diverse applications, the owners of time-and-performance critical applications require cloud service providers’ guarantees about their services, such as availability and response times. Service Level Agreements (SLAs) are a mechanism to communicate and enforce such guarantees typically represented as service level objectives (SLOs), and financial penalties are imposed on SLO violations. Due to delays and inaccuracies caused by manual processing, an automatic method to periodically verify SLA terms in a transparent and trustworthy manner is fundamental to effective SLA monitoring, leading to the acceptance and credibility of such service to the customers of cloud services. This paper presents a blockchain-based distributed infrastructure that leverages fundamental blockchain properties to achieve immutable and trustworthy SLA monitoring within cloud services. The paper carries out an in-depth empirical investigation for the scalability of the proposed system in order to address the challenge of transparently enforcing real-time monitoring of cloud-hosted services leveraging blockchain technology. This will enable all the stakeholders to enforce accurate execution of SLA without any imprecisions and delays by maintaining an immutable ledger publicly across blockchain network. The experimentation takes into consideration several attributes of blockchain which are critical in achieving optimum performance. The paper also investigates key characteristics of these factors and their impact to the behaviour of the system for further scaling it up under various cases for increased service utilization.

Numerous studies show that miss ratios at forward proxies are typically at least 40–50%. This paper proposes and evaluates a new approach for improving the throughput of Web proxy systems by reducing the overhead of handling cache misses. Namely, we propose to front-end a Web proxy with a high performance node that filters the requests, processing the misses and forwarding the hits and the new cacheable content to the proxy. Requests are filtered based on hints of the proxy cache content. This system, called Proxy Accelerator, achieves significantly better communications performance than a traditional proxy system. For instance, an accelerator can be built as an embedded system optimized for communication and HTTP processing, or as a kernel-mode HTTP server. Scalability with the Web proxy cluster size is achieved by using several accelerators. We use analytical models, trace-based simulations, and a real implementation to study the benefits and the implementation tradeoffs of this new approach. Our results show that a single proxy accelerator node in front of a 4-node Web proxy can improve the cost-performance ratio by about 40%. Hint-based request filter implementation choices that do not affect the overall hit ratio are available. An implementation of the hint management module integrated in Web proxy software is presented. Experimental evaluation of the implementation demonstrates that the associated overheads are very small.

Multiple replicas of multimedia objects are distributed to peers in overlay networks. In quorum-based (QB) protocols, every replica may not be up-to-date and the up-to-date replica can be found in the version counter. Multimedia objects are characterized in terms of not only data structure but also quality of service (QoS) parameters like frame rate. A transaction reads a parameter of a replica while there is a type of read operation to read a whole state of a replica. Each parameter of a replica is changed through a write operation. Thus, the data structure and QoS parameters of a replica are independently manipulated. In the multimedia quorum-based (MQB) protocol, multiple replicas of a multimedia object are synchronized based on the newness precedent relation. An object is an encapsulation of data and abstract operations for manipulating the data. There are enriching and impoverishing types of write operations. Some data is added to a replica in an enriching operation. On the other hand, some data in a replica is removed in an impoverishing operation. In order to reduce the overhead to write every replica in a quorum, we take an approach that the state of each replica is not always updated. If a transaction issues an enriching write operation, every replica in the write quorum is updated in the same way as the QB protocol. On the other hand, if an impoverishing write operation is issued, every replica is not updated in the quorum. Impoverishing operations are just recorded in replicas. On receipt of a read operation to read a whole state, impoverishing operations recorded are performed on a replica. The MQB protocol is evaluated in terms of the processing overhead of replicas. We show that the processing overhead of each replica can be reduced in the MQB protocol.

Clouds are heterogeneous service-oriented systems which are increasingly considered as platforms of choice for scientific workflow applications. Because resource and communication failures are inevitable in large complex distributed systems, insuring the reliability of heterogeneous service-oriented systems poses a major challenge. As it affects the quality of user service requirements, reliability has become an important criterion in workflow scheduling. Replication-based fault-tolerance is one approach for satisfying the requirements set to safeguard the reliability of an application. In order to minimize the workflow execution cost while respecting the user-defined deadline and reliability, the present paper proposes Improving CbCP with Replication (ICR) which includes three algorithms: the Scheduling, the Fix Up, and the Task Replication. The Scheduling employs the CbCP algorithm, where CbCP stands for Clustering based on Critical Parent and it is a previously developed algorithm by the same authors, to generate a schedule map of the workflow. The Fix Up algorithm checks the possibility of starting each task earlier in the leased resource without imposing any extra cost. The Task Replication algorithm utilizes the rest of the idle time slots in leased resources to replicate tasks. Experimental results from real and randomly generated applications at different scales demonstrate that the proposed heuristic, for the majority of studied scenarios, increases the execution reliability of workflows while reducing the workflows execution costs.

In order to effectively overcome the disadvantages of the traditional artificial bee colony (ABC) algorithm, i.e., its tendency to fall into local optima and low search speed, an improved ABC algorithm based on the self-adaptive random optimization strategy (SRABC) is proposed. First, the improved algorithm was derived from the self-adaptive method to update the new location of an ABC to improve the correlation within the bee colony. It converges swiftly and obtains the optimal solution for the benchmark function. Second, the bidirectional random optimization mechanism was used to restrain the search direction for the fitness function in order to improve the local search ability. Moreover, the particle swarm optimization algorithm regarded as the initial value of the SRABC algorithm was introduced at the initial stage of the improved ABC algorithm to increase the convergence rate, search precision and searchability, and greatly reduce the search space. Finally, simulation results for benchmark functions show that the proposed algorithm has obviously better performance regarding the search ability and convergence rate, which also prevents early maturing of algorithm.