Routing with multiple quality-of-services constraints: An approximation perspective

This paper focuses on Dynamic Implementation using Array and Linked list. In the data structure concept, the list plays a major role in the allocation of data where it is a general overview of creating a node in a linked list using an array with the initialization of size. The node contains data and is interconnected to the next node in the sequence via their links which perform the search operation where the space and time complexity are not wasted in these analyses. Linked lists are a great way to store a theoretically infinite amount of data with a small and versatile amount of code. The amount of data stored increases linearly with the number of nodes in the list (space-o(n)) where linked lists are more efficient than arrays. It is observed that considering the time complexity when there is a variation in data set linked array is almost reaches close to array whenever dataset is high also linked array has better time complexity than linked list when the searching element is in middle and last. Considering the space complexity linked array is almost 2 times and 4 times less space is needed than array and linked list respectively.

Background: QoS parameters are volatile in nature and possess high nonlinearity, thus making the IoT-based service and recommendation process challenging. Methods: An efficient and accurate forecasting model is lacking in this area and needs to be explored. Though an artificial neural network is a prominent option for capturing such nonlinearities, its efficiency is limited by the structural complexity and iterative learning method. The random vector functional link network (RVFLN) significantly reduces the time complexity by randomly assigning input weights and biases without further modification. Only output layer weights are calculated iteratively by gradient methods or non-iteratively by least square methods. It is an efficient algorithm with low time complexity and can handle complex domain problems without compromising accuracy. Motivated by these characteristics, this article develops an RVFLN-based model for forecasting QoS parameter sequences. Results: Two real-world IoT-enabled web service dataset series are used in developing and evaluating the effectiveness of RVFLN-based forecasts in terms of three performance metrics. Conclusion: Experimental results, comparative studies, and statistical tests are conducted to establish the superiority of the proposed approach over four other similar forecasting techniques.

A faster FPTAS for knapsack problem with cardinality constraint

A service level agreement (SLA) is part of a contract between a cloud service provider (CSP) and a cloud service user (CSU) which defines and describes different agreed properties of the service. The negotiation of the SLA between a CSU and a CSP is a pivotal process in the SLA life cycle. An SLA may include many negotiable quality of service (QoS) parameters with each QoS parameter having multiple acceptable values. Different combinations of acceptable values for all QoS parameters grow exponentially as number of QoS parameters and their selectable values increase. Manually negotiating for all of the QoS parameters considering their various options can be an erroneous and diligent task with lower utility. In this paper, a time efficient flip-flop negotiation strategy for the SLAs in cloud services is presented. The flip-flop negotiation strategy is based on a time dependent 3D utility function and on a dynamic concession strategy using the polynomial extrapolation of opponent's concession. This negotiation strategy is useful for time-critical cloud services as it operates with a motive of reaching an agreement at earlier time without compromising over the utility level of the agreement. Moreover, a multi-provider concurrent negotiation method is presented in this work using the flip-flop negotiation strategy. Multiple experiments are performed (using the implementation of flip-flop negotiation strategy) to test the presented work. The results of the experiments enforce the validity of the flip-flop negotiation strategy for such cloud services where time is an important factor during the SLA negotiation process.

Software-Defined Networking (SDN) is a new efficiently idea of programmable networks that separates the control plane from data plane of all network devices. Internet service provider is responsible for all the control decisions and communication among the forwarding elements from centralized controller. SDN provides the various optimized services. Quality of service (QoS) routing is a path computation method that is suitable for the different traffics generated by several applications, while utilization of network resources has increased. This agreement of service is defined by QoS requirements such as throughput, delay, jitter and packet loss etc. Multimedia applications often require assured from multi QoS constrained, causing the NP-complete problem which cannot be simply solved in polynomial time and high management complexity in the transition network. SDN is able to reduce complexity and it is used to efficiently implement traffic, hence SDN significantly values to development QoS routing. In this paper, we propose QoS routing algorithm called Quantized Level Balance (QLB) for SDN that considers one or many QoS parameters relating to the network application. To satisfy the requirements, QLB selects QoS parameters depending to the level of appropriate application service quality. We have replicated our algorithm on simulate topology with Scalable Video-streaming Evaluation Framework (SVEF). We measure the Peak Signal-to-Noise Ratio (PSNR) and Mean Opinion Score (MOS) of Scalable Video Coding (SVC) at the receiver. Our propose algorithm is improved than single-metric approach that may choose poor QoS parameter paths.

For the grid workflow system include a large of candidate services, the activity scheduling in workflow’s ex-ecution base on quality of service (QoS) constraints can pro-vide optimal service for users. This paper established the QoS’s parameter system with applied technology of grid workflow, and introduced the each parameter’s calculation model of activity’s QoS, the grid work-flow’s QoS estimation method based on the basic flow control structures defined by the abstract grid workflow language (AGWL). The experimental results show that the calculation method in this paper can estimate stably QoS parameter values of grid workflow combining with the multi candidate services, and, can provide a reasonable basis for process scheduling based on QoS constraints.

This paper addresses the issue of supporting quality of service (QoS) parameters in distributed publish-subscribe systems. It advocates that QoS parameters should be handled using the same constructs as other information regarding events, such as their type or content. At the same time, we claim that the use of a consistent set of mechanisms should not preclude to decouple the specification of QoS properties from the specification of type, subject or content-based constraints. We also advocate that QoS parameters should not be embedded on the type or content of the events. We show that some QoS parameters can only be computed in run-time, as they depend on dynamic aspects such as the location of the participants and the system load. The paper proposes a model that supports the decoupling of QoS characterization from the event characterization while, at the same time, offers a uniform treatment of both aspects.

WITHDRAWN: Spearman rank correlation based bagging ensemble bayes optimal classification for genomic predictive pattern analytics

With the rapid growth of functionally identical web services, Quality of Service (QoS) plays vital role for deciding the most suitable services for consumers. Although, QoS for web services has gained extensive attention in the literature, most of the existing efforts are unable to consider the multiperspective QoS of web services. Unlike conventional software paradigms, web services are provided, developed and used by different users such as provider, consumer and broker. As a result, QoS requirements vary from user to user. Existing researches are unable to provide standard solution, which can deal with what service providers, consumers and broker should expose in service description as QoS parameters. Therefore, in this book chapter, a multiperspective PCB-QoS classification of non-functional parameters along with new QoS parameters, i.e. access rate and Overall Aggregated Effective Quality of Service (OAEQoS) is presented. Due to the extensible nature of PCB-QoS classification, it can be extended to accommodate more number of QoS parameters. This QoS classification is based on the idea of partitioning the generic QoS parameters according to multi-user’s perspective. An Average Real Value Sum Method (ARSM) based on default priority constraints is also proposed for ranking of web services that uses the presented QoS classification. With the help of proposed approach, the user can specify the service requirements without taking the hurdle of specifying the weights for each QoS parameter during web service operations. It also prevents the services from malicious service provider to publish the incorrect and inaccurate QoS information. Experimental evaluation shows the effectiveness of proposed approach over the existing approach.

This paper considers the joint design problem of linear precoder, decision feedback equalizer (DFE) and bit allocation for multi-input multi-output (MIMO) broadcast (BC) channels. The problem is formulated as the power minimization problem when the target bit rate and per stream symbol error rate (SER) are specified. For the two-user case, a particular class of joint triangularization (JT) can be applied to obtain the optimal design for the joint optimization problem with quality of service (QoS) constraints, namely, the Minimum Power JT broadcast DFE transceiver (MPJT). For arbitrary number of users, a suboptimal design, the Power Minimized QR DFE broadcast transceiver (PMQR), is also proposed. Numerical results are presented to demonstrate the performance of MPJT and PMQR transceivers under different QoS constraints. 1

Most multirate image processing applications in multihop wireless mesh network (WMN) are delay-sensitive but loss-tolerant. However, joint optimization of image quality and multihop effective capacity (EC) has been largely ignored in the current image transmission schemes in WMN. In this paper, we propose a new quality based cross-layer approach to adaptively optimize the image quality at the receiver side while satisfying the quality of service (QoS) requirements by exploring image position and value of magnitude (P-V) diversity. Specifically, the maximum multihop effective capacity (EC) is determined by QoS parameters and current link status of each path, and then the optimal source coding rate is selected by considering the position and value of magnitude information (P-V) of multirate image processing applications, which significantly increases expected image quality. Simulation results show that the proposed approach achieves better decoded image quality under the same QoS constraints.

A QoS-guaranteed multicast routing protocol

The classic buffer insertion algorithm of van Ginneken has time and space complexity O(n/sup 2/), where n is the number of possible buffer positions. For more than a decade, van Ginneken's algorithm has been the foundation of buffer insertion. In this paper, we present a new algorithm that computes the same optimal buffer insertion, but runs much faster. For 2-pin nets, our time complexity is O(nlogn) and space complexity is O(n). For multipin nets, our time complexity is O(nlog/sup 2/n) and space complexity is O(nlogn). The speedup is achieved by four novel techniques: predictive pruning, candidate tree, fast redundancy check, and fast merging. On industrial test cases, the new algorithms is 2-80 times faster than van Ginneken's algorithm and uses 1/4-1/500 of the memory. Since van Ginneken's algorithm and its variations are used by most existing algorithms on buffer insertion and buffer sizing, our new algorithm significantly improves the performance of all these algorithms. The predictive pruning technique has been applied to buffer cost minimization (Shi et al., 2004), and significantly improved the running time.

Enforcing QoS in scientific workflow systems enacted over Cloud infrastructures

For multimedia applications, the routing algorithms should consider many Quality of Service (QoS) parameters. However, to find routes with two or more QoS parameters is an NP-hard problem. Therefore, recently many researchers are trying to use heuristic methods such as Genetic Algorithm (GA). In a previous work, a QoS multicast routing based on GA was proposed. However, in this algorithm, the multicast routing falls in the local minimum and cannot satisfy the application requirements. In this paper, we propose a new QoS multicast routing protocol, which has better genetic operations than the conventional algorithm, resulting in a better performance.