Bilateral Bargaining Game and Fuzzy Logic in a System Handling SLA-Based Workflows

In the business Grid, the owner of a workflow is assumed to ask an SLA Workflow broker to execute the workflow for him. The price for executing a workflow on the Grid is negotiated between the user and the broker. Determining a price that satisfies both, the user and the SLA workflow broker, is a difficult task. This paper proposes a method using bilateral bargaining game model based on fuzzy logic to determine the price that the user and the broker could accept after the first negotiation round. We also analyze many parameters affecting the price determination process. The validation results show that the approach is suitable with business rules

Multi-User Variability Configuration: a Game Theoretic Approach

Multi-user configuration is a neglected problem in variability-intensive systems area. The appearance of conflicts among user configurations is a main concern. Current approaches focus on avoiding such conflicts, applying the mutual exclusion principle. However, this perspective has a negative impact on users satisfaction, who cannot make any decision fairly. in this work, we propose an interpretation of multi-user configuration as a game theoretic problem. Game theory is a well-known discipline which analyzes conflicts and cooperation among intelligent rational decisionmakers. We present a taxonomy of multi-user configuration approaches, and how they can be interpreted as different problems of game theory. We focus on cooperative game theory to propose and automate a tradeoff-based bargaining approach, as a way to solve the conflicts and maximize user satisfaction at the same time

Automated and dynamic multi-level negotiation framework applied to an efficient cloud provisioning

L’approvisionnement du Cloud est le processus de déploiement et de gestion des applications sur les infrastructures publiques du Cloud. Il est de plus en plus utilisé car il permet aux fournisseurs de services métiers de se concentrer sur leurs activités sans avoir à gérer et à investir dans l’infrastructure. Il comprend deux niveaux d’interaction : (1) entre les utilisateurs finaux et les fournisseurs de services pour l’approvisionnement des applications, et (2) entre les fournisseurs de services et les fournisseurs de ressources pour l’approvisionnement des ressources virtuelles. L’environnement Cloud est devenu un marché complexe où tout fournisseur veut maximiser son profit monétaire et où les utilisateurs finaux recherchent les services les plus efficaces tout en minimisant leurs coûts. Avec la croissance de la concurrence dans le Cloud, les fournisseurs de services métiers doivent assurer un approvisionnement efficace qui maximise la satisfaction de la clientèle et optimise leurs profits.Ainsi, les fournisseurs et les utilisateurs doivent être satisfaits en dépit de leurs besoins contradictoires. La négociation est une solution prometteuse qui permet de résoudre les conflits en comblant le gap entre les capacités des fournisseurs et les besoins des utilisateurs. Intuitivement, la négociation automatique des contrats (SLA) permet d’aboutir à un compromis qui satisfait les deux parties. Cependant, pour être efficace, la négociation automatique doit considérer les propriétés de l’approvisionnement du Cloud et les complexités liées à la dynamicité (dynamicité de la disponibilité des ressources, dynamicité des prix). En fait ces critères ont un impact important sur le succès de la négociation. Les principales contributions de cette thèse répondant au défi de la négociation multi-niveau dans un contexte dynamique sont les suivantes: (1) Nous proposons un modèle de négociateur générique qui considère la nature dynamique de l’approvisionnement du Cloud et son impact potentiel sur les résultats décisionnels. Ensuite, nous construisons un cadre de négociation multicouche fondé sur ce modèle en l’instanciant entre les couches du Cloud. Le cadre comprend des agents négociateurs en communication avec les modules en relation avec la qualité et le prix du service à fournir (le planificateur, le moniteur, le prospecteur de marché). (2) Nous proposons une approche de négociation bilatérale entre les utilisateurs finaux et les fournisseurs de service basée sur une approche d’approvisionnement existante. Les stratégies de négociation sont basées sur la communication avec les modules d’approvisionnement (le planificateur et l’approvisionneur de machines virtuelles) afin d’optimiser les bénéfices du fournisseur de service et de maximiser la satisfaction du client. (3) Afin de maximiser le nombre de clients, nous proposons une approche de négociation adaptative et simultanée comme extension de la négociation bilatérale. Nous proposons d’exploiter les changements de charge de travail en termes de disponibilité et de tarification des ressources afin de renégocier simultanément avec plusieurs utilisateurs non acceptés (c’est-à-dire rejetés lors de la première session de négociation) avant la création du contrat SLA. (4) Afin de gérer toute violation possible de SLA, nous proposons une approche proactive de renégociation après l’établissement de SLA. La renégociation est lancée lors de la détection d’un événement inattendu (par exemple, une panne de ressources) pendant le processus d’approvisionnement. Les stratégies de renégociation proposées visent à minimiser la perte de profit pour le fournisseur et à assurer la continuité du service pour le consommateur. Les approches proposées sont mises en œuvre et les expériences prouvent les avantages d’ajouter la (re)négociation au processus d’approvisionnement. L’utilisation de la (re)négociation améliore le bénéfice du fournisseur, le nombre de demandes acceptées et la satisfaction du client.Cloud provisioning is the process of deployment and management of applications on public cloud infrastructures. Cloud provisioning is used increasingly because it enables business providers to focus on their business without having to manage and invest in infrastructure. Cloud provisioning includes two levels of interaction: (1) between end-users and business providers for application provisioning; and (2) between business providers and resource providers for virtual resource provisioning.The cloud market nowadays is a complex environment where business providers need to maximize their monetary profit, and where end-users look for the most efficient services with the lowest prices. With the growth of competition in the cloud, business providers must ensure efficient provisioning that maximizes customer satisfaction and optimizes the providers’ profit. So, both providers and users must be satisfied in spite of their conflicting needs. Negotiation is an appealing solution to solve conflicts and bridge the gap between providers’ capabilities and users’ requirements. Intuitively, automated Service Level Agreement (SLA) negotiation helps in reaching an agreement that satisfies both parties. However, to be efficient, automated negotiation should consider the properties of cloud provisioning mainly the two interaction levels, and complexities related to dynamicity (e.g., dynamically-changing resource availability, dynamic pricing, dynamic market factors related to offers and demands), which greatly impact the success of the negotiation. The main contributions of this thesis tackling the challenge of multi-level negotiation in a dynamic context are as follows: (1) We propose a generic negotiator model that considers the dynamic nature of cloud provisioning and its potential impact on the decision-making outcome. Then, we build a multi-layer negotiation framework built upon that model by instantiating it among Cloud layers. The framework includes negotiator agents. These agents are in communication with the provisioning modules that have an impact on the quality and the price of the service to be provisioned (e.g, the scheduler, the monitor, the market prospector). (2) We propose a bilateral negotiation approach between end-users and business providers extending an existing provisioning approach. The proposed decision-making strategies for negotiation are based on communication with the provisioning modules (the scheduler and the VM provisioner) in order to optimize the business provider’s profit and maximize customer satisfaction. (3) In order to maximize the number of clients, we propose an adaptive and concurrent negotiation approach as an extension of the bilateral negotiation. We propose to harness the workload changes in terms of resource availability and pricing in order to renegotiate simultaneously with multiple non-accepted users (i.e., rejected during the first negotiation session) before the establishment of the SLA. (4) In order to handle any potential SLA violation, we propose a proactive renegotiation approach after SLA establishment. The renegotiation is launched upon detecting an unexpected event (e.g., resource failure) during the provisioning process. The proposed renegotiation decision-making strategies aim to minimize the loss in profit for the provider and to ensure the continuity of the service for the consumer. The proposed approaches are implemented and experiments prove the benefits of adding (re)negotiation to the provisioning process. The use of (re)negotiation improves the provider’s profit, the number of accepted requests, and the client’s satisfaction

Automated and dynamic multi-level negotiation framework applied to an efficient cloud provisioning

L’approvisionnement du Cloud est le processus de déploiement et de gestion des applications sur les infrastructures publiques du Cloud. Il est de plus en plus utilisé car il permet aux fournisseurs de services métiers de se concentrer sur leurs activités sans avoir à gérer et à investir dans l’infrastructure. Il comprend deux niveaux d’interaction : (1) entre les utilisateurs finaux et les fournisseurs de services pour l’approvisionnement des applications, et (2) entre les fournisseurs de services et les fournisseurs de ressources pour l’approvisionnement des ressources virtuelles. L’environnement Cloud est devenu un marché complexe où tout fournisseur veut maximiser son profit monétaire et où les utilisateurs finaux recherchent les services les plus efficaces tout en minimisant leurs coûts. Avec la croissance de la concurrence dans le Cloud, les fournisseurs de services métiers doivent assurer un approvisionnement efficace qui maximise la satisfaction de la clientèle et optimise leurs profits.Ainsi, les fournisseurs et les utilisateurs doivent être satisfaits en dépit de leurs besoins contradictoires. La négociation est une solution prometteuse qui permet de résoudre les conflits en comblant le gap entre les capacités des fournisseurs et les besoins des utilisateurs. Intuitivement, la négociation automatique des contrats (SLA) permet d’aboutir à un compromis qui satisfait les deux parties. Cependant, pour être efficace, la négociation automatique doit considérer les propriétés de l’approvisionnement du Cloud et les complexités liées à la dynamicité (dynamicité de la disponibilité des ressources, dynamicité des prix). En fait ces critères ont un impact important sur le succès de la négociation. Les principales contributions de cette thèse répondant au défi de la négociation multi-niveau dans un contexte dynamique sont les suivantes: (1) Nous proposons un modèle de négociateur générique qui considère la nature dynamique de l’approvisionnement du Cloud et son impact potentiel sur les résultats décisionnels. Ensuite, nous construisons un cadre de négociation multicouche fondé sur ce modèle en l’instanciant entre les couches du Cloud. Le cadre comprend des agents négociateurs en communication avec les modules en relation avec la qualité et le prix du service à fournir (le planificateur, le moniteur, le prospecteur de marché). (2) Nous proposons une approche de négociation bilatérale entre les utilisateurs finaux et les fournisseurs de service basée sur une approche d’approvisionnement existante. Les stratégies de négociation sont basées sur la communication avec les modules d’approvisionnement (le planificateur et l’approvisionneur de machines virtuelles) afin d’optimiser les bénéfices du fournisseur de service et de maximiser la satisfaction du client. (3) Afin de maximiser le nombre de clients, nous proposons une approche de négociation adaptative et simultanée comme extension de la négociation bilatérale. Nous proposons d’exploiter les changements de charge de travail en termes de disponibilité et de tarification des ressources afin de renégocier simultanément avec plusieurs utilisateurs non acceptés (c’est-à-dire rejetés lors de la première session de négociation) avant la création du contrat SLA. (4) Afin de gérer toute violation possible de SLA, nous proposons une approche proactive de renégociation après l’établissement de SLA. La renégociation est lancée lors de la détection d’un événement inattendu (par exemple, une panne de ressources) pendant le processus d’approvisionnement. Les stratégies de renégociation proposées visent à minimiser la perte de profit pour le fournisseur et à assurer la continuité du service pour le consommateur. Les approches proposées sont mises en œuvre et les expériences prouvent les avantages d’ajouter la (re)négociation au processus d’approvisionnement. L’utilisation de la (re)négociation améliore le bénéfice du fournisseur, le nombre de demandes acceptées et la satisfaction du client.Cloud provisioning is the process of deployment and management of applications on public cloud infrastructures. Cloud provisioning is used increasingly because it enables business providers to focus on their business without having to manage and invest in infrastructure. Cloud provisioning includes two levels of interaction: (1) between end-users and business providers for application provisioning; and (2) between business providers and resource providers for virtual resource provisioning.The cloud market nowadays is a complex environment where business providers need to maximize their monetary profit, and where end-users look for the most efficient services with the lowest prices. With the growth of competition in the cloud, business providers must ensure efficient provisioning that maximizes customer satisfaction and optimizes the providers’ profit. So, both providers and users must be satisfied in spite of their conflicting needs. Negotiation is an appealing solution to solve conflicts and bridge the gap between providers’ capabilities and users’ requirements. Intuitively, automated Service Level Agreement (SLA) negotiation helps in reaching an agreement that satisfies both parties. However, to be efficient, automated negotiation should consider the properties of cloud provisioning mainly the two interaction levels, and complexities related to dynamicity (e.g., dynamically-changing resource availability, dynamic pricing, dynamic market factors related to offers and demands), which greatly impact the success of the negotiation. The main contributions of this thesis tackling the challenge of multi-level negotiation in a dynamic context are as follows: (1) We propose a generic negotiator model that considers the dynamic nature of cloud provisioning and its potential impact on the decision-making outcome. Then, we build a multi-layer negotiation framework built upon that model by instantiating it among Cloud layers. The framework includes negotiator agents. These agents are in communication with the provisioning modules that have an impact on the quality and the price of the service to be provisioned (e.g, the scheduler, the monitor, the market prospector). (2) We propose a bilateral negotiation approach between end-users and business providers extending an existing provisioning approach. The proposed decision-making strategies for negotiation are based on communication with the provisioning modules (the scheduler and the VM provisioner) in order to optimize the business provider’s profit and maximize customer satisfaction. (3) In order to maximize the number of clients, we propose an adaptive and concurrent negotiation approach as an extension of the bilateral negotiation. We propose to harness the workload changes in terms of resource availability and pricing in order to renegotiate simultaneously with multiple non-accepted users (i.e., rejected during the first negotiation session) before the establishment of the SLA. (4) In order to handle any potential SLA violation, we propose a proactive renegotiation approach after SLA establishment. The renegotiation is launched upon detecting an unexpected event (e.g., resource failure) during the provisioning process. The proposed renegotiation decision-making strategies aim to minimize the loss in profit for the provider and to ensure the continuity of the service for the consumer. The proposed approaches are implemented and experiments prove the benefits of adding (re)negotiation to the provisioning process. The use of (re)negotiation improves the provider’s profit, the number of accepted requests, and the client’s satisfaction

Proceedings of The Multi-Agent Logics, Languages, and Organisations Federated Workshops (MALLOW 2010)

http://ceur-ws.org/Vol-627/allproceedings.pdfInternational audienceMALLOW-2010 is a third edition of a series initiated in 2007 in Durham, and pursued in 2009 in Turin. The objective, as initially stated, is to "provide a venue where: the cost of participation was minimum; participants were able to attend various workshops, so fostering collaboration and cross-fertilization; there was a friendly atmosphere and plenty of time for networking, by maximizing the time participants spent together"

Multiagent resource allocation in service networks

The term service network (SN) denotes a network of software services in which complex software applications are provided to customers by aggregating multiple elementary services. These networks are based on the service-oriented computing (SOC) paradigm, which defines the fundamental technical concepts for software services over electronic networks, e.g., Web services and, most recently, Cloud services. For the provision of software services to customers, software service providers (SPs) have to allocate their scarce computational resources (i.e., hardware and software) of a certain quality to customer requests. The SOC paradigm facilitates interoperability over organizational boundaries by representing business relationships on the software system level. Composite software services aggregate multiple software services into software applications. This aggregation is denoted as service composition. The loose coupling of services leads to SNs as dynamic entities with changing interdependencies between services. For composite software services, these dependencies exist across SN tiers; they result from the procurement of services, which are themselves utilized to produce additional services, and constitute a major problem for resource allocation in SNs. If these dependencies are not considered, the fulfillment of agreements may become unaccomplishable (overcommitment). Hence, the consideration of service dependencies is crucial for the allocation of service providers resources to fulfill customer requests in SNs. However, existing resource allocation methods, which could consider these dependencies -- such as combinatorial auctions with a central auctioneer for the whole SN -- are not applicable, since there are no central coordinating entities in SNs. The application of an allocation mechanism that does not consider these dependencies might negatively affect the actual service delivery; results are penalty payments as well as a damage to the reputation of the providers. This research is conducted in accordance to the design science paradigm in information system research. It is a problem-solving paradigm, which targets the construction and evaluation of IT artifacts. The objectives of this research are to develop and evaluate an allocation protocol, which can consider multi-tier service dependencies without the existence of central coordinating entities. Therefore, an interaction protocol engineering (IPE) perspective is applied to solve the problem of multi-tier dependencies in resource allocation. This approach provides a procedure model for designing interaction protocols for multiagent systems, and is closely related to the well-established area of communication protocol engineering. Automated resource allocation in SNs is analyzed in this research by representing the actors as autonomous software agents in the software system. The actors delegate their objectives to their software agents, which conduct the negotiations for service provision on their behalf. Thus, these agents communicate concerning the resource allocation; in this process, the sequence of communication interactions is crucial to the problem addressed. Interaction protocols define a structured exchange of defined messages between agents; they facilitate agent conversations. When multiple agents have to reach agreements by negotiation and bargaining, such as in case with allocating scarce resources, game theory provides means to formalize and analyze the most rational choice of actions for the interacting agents. Based on a formal framework for resource allocation in SNs, this research first performs a game-theoretic problem analysis; it is concerned with the existence, as well as the complexity of computing optimal allocations. In addition, Nash equilibria are analyzed for optimal allocations. Second, a distributed, auction-based allocation protocol, which prevents overcommitments and guarantees socially optimal allocations for single customer requests under certain assumptions, is proposed. Therefore, a game-theoretic model and an operationizable specification of the protocol are presented. Third, it is formally verified that the protocol enables multi-tier resource allocation and avoids overcommitments by proofs for the game-theoretic model and by model checking for the interaction protocol specification; using the model checker Spin, safety properties like the absence of deadlock are as well formally verified as the protocol enabling multi-tier resource allocation. Fourth, the efficacy and the benefits of the proposed protocol are demonstrated by multiagent simulation for concurrent customers. The experimental evaluation provides evidence of the protocols efficiency compared to the socially optimal allocation as a centralized benchmark in different settings, e.g., network topologies and different bidding policies.Der Begriff Service Network (SN) bezeichnet ein Netzwerk von Software-Services, in dem komplexe Software-Applikationen durch Aggregation mehrerer elementarer Services für Kunden bereitgestellt werden. Diese Netzwerke basieren auf dem Paradigma des Service-oriented Computing, welches die grundlegenden technischen Konzepte für Software-Services über elektronische Netzwerke bereitstellt, d.h. Web Services und zuletzt Cloud-Computing. Für die Bereitstellung von Software-Services für Kunden müssen Software-Anbieter ihre knappen Ressourcen (d.h. Hardware und Software) einer bestimmten Qualität zu Kundenanfragen allozieren, also entsprechende Ressourcen reservieren, um Software-Services in der vereinbarten Dienstgüte bereitzustellen. Zusammengesetzte Software-Services aggregieren mehrere Software-Services zu Software-Applikations-Services. Diese Aggregation wird als Service-Komposition bezeichnet. Die lose Kopplung von Services macht SNs zu dynamischen Entitäten mit sich verändernden Interdependenzen zwischen den Services. Für zusammengesetzte Software-Services existieren solche Abhängigkeiten über mehrere SN-Stufen; sie ergeben sich durch die Beschaffung von Services, welche für die Produktion von weiteren Services verwendet werden, und stellen ein Hauptproblem bei der Ressourcenallokation in SN dar. Werden diese Abhängigkeiten nicht berücksichtigt, kann die Erfüllung von Vereinbarungen undurchführbar werden (overcommitment). Daher ist die Berücksichtigung von Service-Abhängigkeiten bei der Allokation von Ressourcen der Service-Anbieter für die Erfüllung der Kundenanfragen in SNs entscheidend. Existierende Methoden der Ressourcenallokation, welche diese Abhängigkeiten berücksichtigen könnten -- wie kombinatorische Auktionen mit einem zentralen Auktionator für das gesamte SN -- sind jedoch nicht anwendbar, da in SNs keine zentralen Koordinationsentitäten existieren. Der Einsatz eines Allokationsmechanismus, welcher diese Abhängigkeiten nicht berücksichtigt, kann die konkrete Service-Erbringung negativ beeinflussen und somit in Strafzahlungen und einer Beeinträchtigung der Reputation der Service-Anbieter resultieren. Die vorliegende Forschungsarbeit wird in Übereinstimmung mit dem Design Science-Paradigma durchgeführt. Dabei handelt es sich um ein Problemlösungs-Paradigma, welches die Konstruktion und Evaluation von IT-Artefakten zum Ziel hat. Ziel dieser Forschungsarbeit ist die Entwicklung und Evaluation eines Allokationsprotokolls, welches mehrstufige Service-Abhängigkeiten ohne die Existenz zentraler, koordinierender Entitäten berücksichtigen kann. Zu diesem Zweck wird eine Interaction-Protocol-Engineering (IPE)-Perspektive eingenommen, um das Problem mehrstufiger Abhängigkeiten bei der Ressourcenallokation zu lösen. Dieser Ansatz stellt ein Vorgehensmodell für den Entwurf von Interaktionsprotokollen für Multiagentensysteme zur Verfügung. Diese Forschungsarbeit analysiert die automatisierte Ressourcenallokation in SNs durch die Repräsentation der Akteure als autonome Softwareagenten im Softwaresystem. Die Akteure delegieren ihre Ziele an ihre Softwareagenten, welche in deren Auftrag die Verhandlung für die Service-Erbringung durchführen. Somit kommunizieren diese Softwareagenten bezüglich der Ressourcenallokationen; dabei ist die Abfolge der Interaktionen für das adressierte Problem elementar. Interaktionsprotokolle definieren einen strukturierten Austausch bestimmter Nachrichten zwischen Agenten. Wenn mehrere Agenten Vereinbarungen durch Verhandlungen treffen müssen, wie im Falle der Allokation knapper Ressourcen, stellt die Spieltheorie Methoden bereit, um rationale Entscheidungen der Aktionen für interagierende Agenten zu analysieren. Basierend auf einem formalen Modell für Ressourcenallokation in SN führt diese Forschungsarbeit eine spieltheoretische Problemanalyse durch. Hierbei werden insbesondere mehrstufige Abhängigkeiten von Vereinbarungen berücksichtigt. Die Problemanalyse befaßt sich mit der Existenz sowie der Komplexität der Berechnung optimaler Allokationen. Es wird ein verteiltes, Auktions-basiertes Allokationsprotokoll, welches overcommitments vermeidet, vorgeschlagen. Basierend auf dem spieltheoretischen Modell wird gezeigt, daß das vorgeschlagene Protokoll overcommitments vermeidet und sozial optimale Allokationen für einzelne Kundenanfragen unter bestimmten Annahmen garantiert. Darüber hinaus wird der Modellprüfer Spin verwendet, um bestimmte formale Eigenschaften der Beschreibung des Protokolls zu beweisen. Abschließend werden die Anwendbarkeit und der Nutzen des vorgeschlagenen Protokolls mittels Multiagentensimulation demonstriert. In den Simulationsexperimenten wird die Effizienz des Protokolls mit der optimalen Allokation als zentralisiertes Benchmark in unterschiedlichen Einstellungen (z.B. Netzwerktopologien oder Anzahl von Kunden- und Anbieter-Agenten) für verschiedene Bietrichtlinien für Anbieter verglichen

Service level agreement specification for IoT application workflow activity deployment, configuration and monitoring

PhD ThesisCurrently, we see the use of the Internet of Things (IoT) within various domains such as healthcare, smart homes, smart cars, smart-x applications, and smart cities. The number of applications based on IoT and cloud computing is projected to increase rapidly over the next few years. IoT-based services must meet the guaranteed levels of quality of service (QoS) to match users’ expectations. Ensuring QoS through specifying the QoS constraints using service level agreements (SLAs) is crucial. Also because of the potentially highly complex nature of multi-layered IoT applications, lifecycle management (deployment, dynamic reconfiguration, and monitoring) needs to be automated. To achieve this it is essential to be able to specify SLAs in a machine-readable format. currently available SLA specification languages are unable to accommodate the unique characteristics (interdependency of its multi-layers) of the IoT domain. Therefore, in this research, we propose a grammar for a syntactical structure of an SLA specification for IoT. The grammar is based on a proposed conceptual model that considers the main concepts that can be used to express the requirements for most common hardware and software components of an IoT application on an end-to-end basis. We follow the Goal Question Metric (GQM) approach to evaluate the generality and expressiveness of the proposed grammar by reviewing its concepts and their predefined lists of vocabularies against two use-cases with a number of participants whose research interests are mainly related to IoT. The results of the analysis show that the proposed grammar achieved 91.70% of its generality goal and 93.43% of its expressiveness goal. To enhance the process of specifying SLA terms, We then developed a toolkit for creating SLA specifications for IoT applications. The toolkit is used to simplify the process of capturing the requirements of IoT applications. We demonstrate the effectiveness of the toolkit using a remote health monitoring service (RHMS) use-case as well as applying a user experience measure to evaluate the tool by applying a questionnaire-oriented approach. We discussed the applicability of our tool by including it as a core component of two different applications: 1) a contextaware recommender system for IoT configuration across layers; and 2) a tool for automatically translating an SLA from JSON to a smart contract, deploying it on different peer nodes that represent the contractual parties. The smart contract is able to monitor the created SLA using Blockchain technology. These two applications are utilized within our proposed SLA management framework for IoT. Furthermore, we propose a greedy heuristic algorithm to decentralize workflow activities of an IoT application across Edge and Cloud resources to enhance response time, cost, energy consumption and network usage. We evaluated the efficiency of our proposed approach using iFogSim simulator. The performance analysis shows that the proposed algorithm minimized cost, execution time, networking, and Cloud energy consumption compared to Cloud-only and edge-ward placement approaches

Combining SOA and BPM Technologies for Cross-System Process Automation

This paper summarizes the results of an industry case study that introduced a cross-system business process automation solution based on a combination of SOA and BPM standard technologies (i.e., BPMN, BPEL, WSDL). Besides discussing major weaknesses of the existing, custom-built, solution and comparing them against experiences with the developed prototype, the paper presents a course of action for transforming the current solution into the proposed solution. This includes a general approach, consisting of four distinct steps, as well as specific action items that are to be performed for every step. The discussion also covers language and tool support and challenges arising from the transformation

Supply Chain

Traditionally supply chain management has meant factories, assembly lines, warehouses, transportation vehicles, and time sheets. Modern supply chain management is a highly complex, multidimensional problem set with virtually endless number of variables for optimization. An Internet enabled supply chain may have just-in-time delivery, precise inventory visibility, and up-to-the-minute distribution-tracking capabilities. Technology advances have enabled supply chains to become strategic weapons that can help avoid disasters, lower costs, and make money. From internal enterprise processes to external business transactions with suppliers, transporters, channels and end-users marks the wide range of challenges researchers have to handle. The aim of this book is at revealing and illustrating this diversity in terms of scientific and theoretical fundamentals, prevailing concepts as well as current practical applications