Showing papers on "Differentiated service published in 2016"

Network slicing as a service: enabling enterprises' own software-defined cellular networks

Abstract: With the blossoming of network functions virtualization and software-defined networks, networks are becoming more and more agile with features like resilience, programmability, and open interfaces, which help operators to launch a network or service with more flexibility and shorter time to market. Recently, the concept of network slicing has been proposed to facilitate the building of a dedicated and customized logical network with virtualized resources. In this article, we introduce the concept of hierarchical NSaaS, helping operators to offer customized end-to-end cellular networks as a service. Moreover, the service orchestration and service level agreement mapping for quality assurance are introduced to illustrate the architecture of service management across different levels of service models. Finally, we illustrate the process of network slicing as a service within operators by typical examples. With network slicing as a service, we believe that the supporting system will transform itself to a production system by merging the operation and business domains, and enabling operators to build network slices for vertical industries more agilely.

Designing public services: the usefulness of three service design methods for identifying user experiences

Abstract: This article examines the use of three service design methods in exploring complex public service systems. The methods used were the persona technique, mapping techniques in collaborative design workshops, and observations supplemented by group discussions. In their application to a university service, it was found that through their user-centred and collaborative approach, the service design methods assisted in the analysis of user experiences, including critical incidents, within the service system. It was also identified that user co-production formed the core of the service system and its processes, which highlights the need to actively involve users in public service design projects.

Method and apparatus for customer service management for a wireless communication network

Abstract: A method and system for providing Customer Service Management (CSM) a communication network, such as a 5G wireless communication network. The communication network provides at least one service involving one or more terminals serviced by the communication network. A CSM function is defined which is based upon said at least one service and customized to said at least one service, to provide service-customized CSM. CSM may provide service-based charging/billing, service-based context management, service-customized QoE control, service-customized network topology.

A service selection model for digital music service platforms using a hybrid MCDM approach

Abstract: Display OmittedThe improvement strategy map for digital music platform service. We concluded the selection criteria for customers to evaluate and select music services by discovering the customers' needs and intentions of the music service.We proposed the service selection model for digital music platform service based on a hybrid MCDM approach.This service selection model applied to rank and improve the four digital music platform services for getting the best service selection.This study proposed the key driving aspect for platform services of digital music based on the NRM and rank them by using the model proposed.Not only can the conclusions be served as some suggestions for service providers to improve existing functions but also to plan further utilities for platform service of digital music in the next generation. Digital music services have provided more and more digital contents and service styles. The number of people paying to download music is on the rise. Digital music files, mainly in MP3 format, have become widespread on the internet. Downloading digital products for free may harm creators and music publishers, because it is very easy to obtain free-music through peer-to-peer sharing technologies over the internet. At the same time, portable entertainment devices and mobile phones are now able to carry music files, enabling people to access music much more easily. On the other hand, with the coming of the 5G in the telecom infrastructure, the rise in downloading music using mobile devices becomes possible. People can access online-music platform services through cable/ADSL with their digital devices (e.g., Personal computer, Notebook and Smart phone) or through the telecom services accompanying their mobile devices. Therefore, a critical issue for record publishers, or digital music service providers, is how to provide services to create value and fulfill customer needs. By determining customer music service needs and intentions, this study identifies the selection criteria necessary for customers to evaluate and select digital music service platforms. A novel MCDM (Multiple Criteria Decision Making) technique is developed that integrates the Decision making Trial and Evaluation Laboratory (DEMATEL), Principal Component Analysis (PCA), Analytical Network Procedure (ANP), and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). This technique ranks and improves the digital music service platforms to obtain the best win-win service selection. This paper will propose the key driving aspects of the digital music service platforms and rank them by using the model proposed. The conclusions are composed of suggestions for service providers to improve their existing functions and plan further utilities for the digital music service platforms.

Two-stage approach for reliable dynamic Web service composition

Abstract: This paper proposes a two-stage method for reliable dynamic Web service composition and improves the reliability of dynamic Web service composition.In the first stage, the scale of candidate services is reduced and the service composition problem is transformed to local service selection problem.In the second stage, QoS of candidate services are predicted and used to select the optimal services for tasks in the service composition workflow.Culture Genetic Algorithm (CGA) is proposed to reduce candidate services and decompose the global QoS constraints into local QoS constraints.It proposes a Web service QoS dynamic prediction method based on improvedÂ?case-based reasoning (CBR). Web service composition is a key technology for creating value-added services by integrating available services. With the rapid development of Service Computing, Cloud Computing, Big Data, and the Internet of Things, mass services with the same functionalities and different quality of service (QoS) values are available on the Internet. Moreover, due to the uncertainties of services' application environment, a service's QoS is highly dynamic; these two factors cause reliable dynamic Web service composition to be a challenge. To address this issue, this paper proposes a two-stage approach for reliable dynamic Web service composition. In the first stage, the top K Web service composition schemes based on each service's historical QoS values are selected with the proposed algorithm named Culture Genetic Algorithm (CGA). Then, component services in the top K schemes are filtered out and employed as the candidate services for dynamic service composition. This operation can greatly reduce the number of available services and filter out better candidate services for dynamic service composition. Next, the global QoS constraints are decomposed into local QoS constraints with the CGA algorithm, and the global optimal problem of service composition is transformed into a local optimal service selection problem; this conversion increases the flexibility of dynamic service composition and provides a chance to predict QoS values of services before service selection. In the second stage, before selecting the best service for each task during the running of the service composition workflow, QoS values of each candidate service are predicted based on the improved case-based reasoning, and the best service is selected according to the predicted QoS values. Through QoS prediction, the reliability of the composite Web service can be greatly enhanced. Finally, experimental results show that the proposed method is feasible and effective.

Trust model at service layer of cloud computing for educational institutes

Abstract: Cloud computing is one of those technologies which have revolutionized the modern world. Through this, people can start their businesses without huge investments required for infrastructure like servers, technical staff for maintenance, and purchasing of expensive software, etc. With many advantages, there are few risks involved with cloud computing. There are issues like unavailability of service, i.e., they are down when required. Another issue is of outdated service/stuff provision to the clients by the cloud service providers. Similarly, lacking of effective and quality support services to their customers is another important concern. Moreover, non-capability of cloud service provider in honoring the service level agreement is an additional prong in this list. All such issues make cloud service users frustrated. Hence, there is a need of a system which may help the cloud service user to select good cloud service provider. Hence, for the above mentioned issues, in this article, we have proposed a model which will help the cloud service users in finding out the efficient and trustworthy cloud service provider. In put data to the model can be collected from regulatory authorities, performance of cloud service provider in the last one year, and feedback taken from the customers. Moreover, the proposed model is flexible enough to be customized according to the precedence level of aforementioned parameters for the cloud service users, i.e., educational institutes. We have also given a comparative analysis of proposed model with general existing model to portray the importance and requirement of the designed model for the said application domain.

An ontology pattern language for service modeling

Abstract: The notion of service spans several domains, such as healthcare, education, and information and communication technology (ICT). In this context, service ontologies are very useful for establishing a common understanding of the main concepts and relations involved, as well as for serving as basis for modeling services in different domains. In this paper, we present an Ontology Pattern Language, called S-OPL, providing a network of interconnected ontology modeling patterns covering the core conceptualization of services. S-OPL builds on UFO-S, a commitment-based core ontology for services. S-OPL patterns support modeling types of customers and providers, as well as the main service life-cycle phases, namely: service offering, service negotiation/agreement, and service delivery. The use of S-OPL is demonstrated in a real case in the ICT service domain.

Multi-Phase Ant Colony System for Multi-Party Data-Intensive Service Provision

Abstract: The rapid proliferation of enormous sources of digital data has led to greater dependence on data-intensive services Each service may actually request or create a large amount of data sets To compose these services will be more challenging Issues such as autonomy, scalability, adaptability, and robustness, become difficult to resolve In order to automate the process of reaching an agreement among service composers, service providers, and data providers, an ant-inspired negotiation mechanism is considered in this paper We exploit a group of agents automatically negotiating to establish agreeable service contracts Two-stage negotiation procedures are used in our data-intensive service provision model, which will provide effective and efficient service selection for service composers We also present a multi-phase, multi-party negotiation protocol, where the ant colony system is applied to select services with the best or near-optimal utility outputs In order to adapt the ant colony system to handle the dynamic scenarios during negotiations, we also discuss several strategies for modifying the pheromone information in the first place The experimental results show that our negotiation-based approach can facilitate the data-intensive service provision with better outcome

Robust Service Compositions with Functional and Location Diversity

Abstract: Service composition provides a means of customized and flexible integration of service functionalities. Quality-of-service (QoS) optimization algorithms select services to adapt workflows to the non-functional requirements of the user. With increasing number of services in a workflow, previous approaches fail to achieve a sufficient reliability. Moreover, expensive ad-hoc replanning is required to deal with service failures. The major problem with such sequential application of planning and replanning is that it ignores the potential costs during the initial planning and they consequently are hidden from the decision maker. Our idea to overcome this problem is to compute a QoS optimized selection of service clusters that includes a sufficient number of backup services for each service employed. These backup services should be sufficiently distributed to prevent a task failure in case of, e.g., a network failure. To support the decision maker in the selection task, our multi-objective approach considers the possible repair costs directly in the initial composition. Our graphical user interface visualizes the resulting QoS of the workflow and the location of the services to enable the decision maker to select compositions in line with risk preferences. We prove the benefits of our approach in our detailed evaluation.

Distributed denial of service attack detection using Naive Bayes Classifier through Info Gain Feature Selection

Abstract: Distributed Denial of Service (DDoS) attack brings revenue loss, productivity loss, reputation damage, theft, etc. to huge banking and business firms. This leads to the necessity of a good DDoS prevention and detection techniques. The paper aims to provide a better solution to these problems using features analysis. The statistical characteristics or parameters of the incoming packets viz. MTI (mean time intervals), POIP (probability of occurrence of IP), TTL (time to live), ACK value, SYN value, time stamp field, differentiated service field and sequence number are analyzed. The incoming packets are classified into normal and attack packets by deploying Naive Bayes classifier algorithm using the attack and normal profile from previously available datasets. Information gain algorithm is used to decrease the computation time, memory usage and increase efficiency of detection by reducing the number of parameters. The performance increases with more consistency after the application of information gain. The efficiencies of detection before and after the application of information gain are 98% and 99.5% respectively. The computation time is also reduced by 46.6%. In the paper, we use CAIDA 2008 and CAIDA anonymous trace 2015 datasets for feature selection and classification.

Method, system, and program storage device for managing tenants in an industrial internet of things

Abstract: In an example embodiment, a method, system, and program storage device for binding an industrial application to a plurality of services in an Industrial Internet of Things (IIoT) is provided. For each of a plurality of tenants, a service template corresponding to a group in which the corresponding tenant belongs is retrieved and an instance of the industrial application is instantiated for the corresponding tenant. Then, at runtime of an instance of the industrial application, a number of actions are taken. A request by the instance of the industrial application for a service identified by a first service name is detected. Then a credential for the service name is retrieved, with the credential identifying a location where an instance of the service identified by the first service name resides. The service identified by the first service name is then dynamically called using the location.

QoS ontology for service selection and reuse

Abstract: Web service technologies become popular in software development in all sectors. Variety services related standards are defined but they still have limitations to represent the services such as the service registry does not support the Quality of Service (QoS) properties, web service description language does not allow specifying the QoS properties and there is no common ontology's structure to store services. Our research aims to enhance the representation of services to assist the service selection and composition process in order to reduce the development costs. The existing resources are analyzed to define a web service ontology (WSOnto). Furthermore, a service selection algorithm is proposed to validate the proposed WSOnto. It considers the multiple criteria of inputs such as: context, functional and non-functional properties of services. The WSOnto and a service selection algorithm are studied to assist the re-engineering of business processes from users' designed business processes.

Meta-heuristics for placing strategic safety stock in multi-echelon inventory with differentiated service times

Abstract: The computational resolution of multi-echelon safety stock placement problems has attracted ample attention in recent years. Practitioners can obtain good solutions for large supply networks with general structure using the guaranteed service model. The mainstream assumption in this model is that a stock point quotes identical service times to its successors. In business, it is common to assign customers to different customer- and service classes, as it can yield significant cost improvements. Nevertheless, differentiated service times have rarely been considered in computational methods of safety stock placement. We relax the assumption of identical service times in the guaranteed service approach and allow stock points to prioritize between their successors. This increases the complexity of the problem considerably, so that meta-heuristics become the methods of choice. Meta-heuristics need a mapping between safety stock levels in the supply network (from which they compute the holding cost) and an internal representation of stocking decisions (from which they generate new solutions). The design of a representation is non-trivial because of complex interactions between stocking decisions and stock levels. We propose a representation for the safety stock allocation problem with differentiated service times that can be used in general-acyclic supply networks. We apply a local search, a simple genetic algorithm and a problem-adjusted simulated annealing to 38 general-acyclic real-world instances. Results suggest that service time differentiation indeed decreases total holding cost in the network. Simulated annealing outperforms the other meta-heuristics within the set of tested methods with respect to speed and solution quality.

QSCAS: QoS Aware Web Service Composition Algorithms with Stochastic Parameters

Abstract: In recent times, automated business processes and web service technologies have become popular and ubiquitous for catering to diverse user needs. While providing a service, the service providers are typically expected to furnish promised QoS values for the services they deliver. However, when the services are physically deployed and invoked during a query resolution, these parameter values vary largely depending on different factors like network load, number of applications running in the server etc. In this work, we present a stochastic model of the web service composition problem. Experimental results on Web Service Challenge (WSC) benchmarks show the efficiency of our proposed mechanism.

Efficient Modeling and Demand Allocation for Differentiated Cloud Virtual-Network as-a Service Offerings

Abstract: Cloud clients (CCs) of current distributed cloud applications are still not assured of their service quality, in particular, in terms of the experienced latency. Unfortunately, this is mainly attributed to the unpredictability of the communication links among their hosting distributed data centers. To address this problem, this article introduces a novel virtual-network-as-a-service (VNaaS) model to host these applications. In contrast to existing randomly or statically provisioned inter-data centers bandwidth sharing models, the proposed model allows CCs to accurately express their varying network resources needs, demand constraints and tolerance to the cloud latency. In turn, the model maps these requirements to create inter-data centers virtual links hosting each multiple virtual pipes with differentiated service qualities to carry the CC's various traffic flows. To aid the CCs in optimally determining their VNaaS demands, given the budget constraints of their hosted applications, we also develop a novel demand selection scheme based on a two stage-budget allocation mechanism. In the first budgeting stage, the CC calculates an optimal effective service rate for each of its virtual link along with a corresponding link budget and price index. In the second stage, the virtual link budget is distributed to purchase bandwidth for the link's virtual pipes, each with a given service quality and pricing. We then extend the proposed model to allow the CC to enforce any required virtual links’ capacity constraints on the effective service rates resulting from the traffic matrix on the VNaaS. Finally, we develop corresponding differentiated VNaaS pricing and service monitoring mechanisms that can be employed by the cloud service provider (CSP) to regulate the offerings and demands of the distributed cloud services. Performance evaluation results demonstrate the significant improvement in the service quality, the higher utilization of the cloud resources and the increase in the CSP's net profit.

A Feature-Based Framework for Developing and Provisioning Customizable Web Services

Abstract: A customizable web service is a service that enables service consumers to dynamically determine variants of the service they receive. Provisioning customizable services helps to efficiently address functional variability in customer requirements. However, this is challenging due to: i) the complexity in deriving the right subset of service capabilities for a service variant and ii) the existence of a large number of variants and their dependencies. We propose a feature-based framework to tackle this challenge. In our framework, a feature model is used to capture functional variability in customer requirements at a high-level of abstraction and to provide customers with a much simpler way to customize an atomic service. A service engineering process is designed to facilitate the systematic identification and implementation of variability during service development, and to maintain the mapping between variabilities at the feature modeling level and the service implementation level. We define a generative middleware that supports service deployment and exploits the mapping to enable runtime service customization. A large scale case study based on the Amazon web services is used for evaluation. In addition to addressing the challenge in provisioning customizable services, our experiments show that the generative middleware helps to reduce runtime resource consumption.

Systems and methods for efficiently handling appliance warranty service events

Abstract: An automated event management system for smart appliances residing at locations of owners and communicatively connected to respective smart-appliance event-reporting platforms includes a service response platform and an enterprise resource platform The service response platform receives appliance event messages from respective ones of the smart appliances and normalizes them into outbound service call requests having a standardized format and determines an appropriate responsive action to the outbound service call request by accessing data including past information and performing a triage to determine root failures Based upon the determination a trade and replacement parts are selected After repair information is gathered to diagnose that repair and improve the data for future use The enterprise resource platform manages the service providers by scheduling service calls directly in calendars, by dispatching the providers, by selecting replacement parts and communicating with the owners regarding the service call, and by transmitting the service call data

Electronic and in-person service quality of hybrid services

Abstract: The service industries have experienced dramatic changes in service delivery format because of fast-paced innovation in information technology. Hybrid services involve service deliveries through conventional and technology-enabled environments, each of which is complementary and non-interchangeable. However, limited research has examined consumer behavior in response to a series of relevant service episodes in different channels at different points in time. In other words, how customers perceive service quality at each service encounter and how the cumulative effect of these perceptions influences customers’ overall service value assessment and satisfaction remain unclear. This study addresses this research gap by investigating the sequential influence of e-service quality on in-person service quality in a hybrid service format in which interpersonal and computer-mediated services coexist but at different points in time. Empirical analysis shows that e-service quality directly and positively affec...

An Approach of Service Discovery Based on Service Goal Clustering

Abstract: The increasing amount of services published on the Web makes it difficult to discover relevant services for users. Unlike the SOAP-based services that are described by structural WSDL documents, RESTful services, the most popular type of services, are mainly described using short texts. The keyword-based discovery technology for RESTful services adopted by existing service registries is insufficient to obtain accurate services according to user requirements. Moreover, it remains a difficult task for users to specify queries that perfectly reflect their requirements due to the lack of knowledge of their expected service functionalities. In this paper, we propose a goal-oriented service discovery approach, which aims to obtain accurate RESTful services for user functional goals. The approach first groups existing services into clusters using topic models. It then clusters the service goals extracted from the textual descriptions of services by leveraging the topic model trained for services. Based on the service goal clusters, our approach can help users refine their initial queries by recommending similar service goals. Finally, relevant services are obtained by matching the service goals selected by users with those of existing services. Experiments conducted on a real-world service dataset crawled from ProgrammableWeb show the effectiveness of the proposed approach.

An efficient algorithm for partially matched services in internet of services

Abstract: Internet of Things (IoT) connects billions of devices in an Internet-like structure. Each device encapsulated as a real-world service which provides functionality and exchanges information with other devices. This large-scale information exchange results in new interactions between things and people. Unlike traditional web services, internet of services is highly dynamic and continuously changing due to constant degrade, vanish and possibly reappear of the devices, this opens a new challenge in the process of resource discovery and selection. In response to increasing numbers of services in the discovery and selection process, there is a corresponding increase in number of service consumers and consequent diversity of quality of service (QoS) available. Increase in both sides' leads to the diversity in the demand and supply of services, which would result in the partial match of the requirements and offers. This paper proposed an IoT service ranking and selection algorithm by considering multiple QoS requirements and allowing partially matched services to be counted as a candidate for the selection process. One of the applications of IoT sensory data that attracts many researchers is transportation especially emergency and accident services which is used as a case study in this paper. Experimental results from real-world services showed that the proposed method achieved significant improvement in the accuracy and performance in the selection process.

Cluster-Based Web Service Recommendation

Abstract: The concept of Web services has become a widely applied paradigm in research and industry, with the number of services published on the Internet increasing rapidly over the last few years. Thus, service recommendation is becoming a challenging and time-consuming task due to large search space. Organizing the Web services into clusters is a one of very efficient approach for search space pruning process. In this paper, we proposed cluster-based service recommendation approach. User may want to interact with services that have similar functionalities, which they used to interact. Thus, we consider semantic similarity between services as one factor in the clustering process. Further, user may be interesting to identify the appropriate services to generate value-added service. Thus, we consider the association between services as the second factor. Our approach recommend services for currently invoked service using the generated clusters and services with better QoS values selected by a filtering process. Experimental results show that our approach works effectively.

System and method for service orchestration in distributed cloud environment

Abstract: The present invention relates to a system and a method for service orchestration capable of integrating network resources distributed in a cloud network to provide a service required by a service provider. The method includes: receiving a service profile from a service provider; analyzing the received service profile, and generating information on a virtual function and an application server used to provide a service as a service specification; setting a service flow to provide the service to a user based on the service specification; and transmitting a service execution control command according to the service flow to at least one micro data centre.

Semantic Agent-Based Service Middleware and Simulation for Smart Cities

Abstract: With the development of Machine-to-Machine (M2M) technology, a variety of embedded and mobile devices is integrated to interact via the platform of the Internet of Things, especially in the domain of smart cities. One of the primary challenges is that selecting the appropriate services or service combination for upper layer applications is hard, which is due to the absence of a unified semantical service description pattern, as well as the service selection mechanism. In this paper, we define a semantic service representation model from four key properties: Capability (C), Deployment (D), Resource (R) and IOData (IO). Based on this model, an agent-based middleware is built to support semantic service enablement. In this middleware, we present an efficient semantic service discovery and matching approach for a service combination process, which calculates the semantic similarity between services, and a heuristic algorithm to search the service candidates for a specific service request. Based on this design, we propose a simulation of virtual urban fire fighting, and the experimental results manifest the feasibility and efficiency of our design.