As the Internet has grown in size and importance to society, it has become increasingly difficult to generate global metrics of interest that can be used to verify proposed algorithms or monitor performance. This dissertation tackles the problem by proposing several novel algorithms designed to perform Internet-wide measurements using existing or inexpensive resources. We initially address distance estimation in the Internet, which is used by many distributed applications. We propose a new end-to-end measurement framework called Turbo King (T-King) that uses the existing DNS infrastructure and, when compared to its predecessor King, obtains delay samples without bias in the presence of distant authoritative servers and forwarders, consumes half the bandwidth, and reduces the impact on caches at remote servers by several orders of magnitude. Motivated by recent interest in the literature and our need to find remote DNS nameservers, we next address Internet-wide service discovery by developing IRLscanner, whose main design objectives have been to maximize politeness at remote networks, allow scanning rates that achieve coverage of the Internet in minutes/hours (rather than weeks/months), and significantly reduce administrator complaints. Using IRLscanner and 24-hour scan durations, we perform 20 Internet-wide experiments using 6 different protocols (i.e., DNS, HTTP, SMTP, EPMAP, ICMP and UDP ECHO). We analyze the feedback generated and suggest novel approaches for reducing the amount of blowback during similar studies, which should enable researchers to collect valuable experimental data in the future with significantly fewer hurdles. We finally turn our attention to Intrusion Detection Systems (IDS), which are often tasked with detecting scans and preventing them; however, it is currently unknown how likely an IDS is to detect a given Internet-wide scan pattern and whether there exist sufficiently fast stealth techniques that can remain virtually undetectable at large-scale. To address these questions, we propose a novel model for the windowexpiration rules of popular IDS tools (i.e., Snort and Bro), derive the probability that existing scan patterns (i.e., uniform and sequential) are detected by each of these tools, and prove the existence of stealth-optimal patterns.

This thesis, studies automated methods to achieve web service advertisement and discovery, and presents efficient search and matching techniques based on OWL-S. In the proposed system, the service discovery and matchmaking is performed via a centralized peer-to-peer web service repository. The repository has the ability to run on a software cloud, which improves the availability and scalability of the service discovery. The service advertisement is done semi-automatically on the client side, with an automatic WSDL to OWL-S conversion, and manual service description annotation. An OWL-S based unified ontology -Suggested Upper Merged Ontology- is used during annotation, to enhance semantic matching abilities of the system. The service advertisement and availability are continuously monitored on the client side to improve the accuracy of the query results. User-agents generate query specification using the system ontology, to provide semantic unification between the client and the system during service discovery. Query matching is performed via complex Hilbert Spaces composed of conceptual planes and categorical similarities for each web service. User preferences following the service queries are monitored and used to improve the service match scores in the long run.

Adhoc networks do not depend on any fixed infrastructure. The most outstanding features of adhoc networks are non-centralized structure and dynamic topology change due to high mobility. Since mentioned dynamics of mobile adhoc networks complicate reaching the resources in the network, service discovery is significantly an important part of constructing stand-alone and self-configurable mobile adhoc networks. The heterogeneity of the devices and limited resources such as battery are also load up more difficulty to service discovery. Due to the volatile nature of the adhoc networks, service discovery algorithms proposed for mobile and adhoc networks suffer from some problems. Scalability becomes a problem when the service discovery is based on flooding messages over the network. Furthermore, the high traffic which occurs due to the message exchange between network nodes makes the communication almost impossible. Partitioning a network into sub-networks is an efficient way of handling scalability problem. In this thesis, a mobility based service discovery algorithm for clustered MANET is presented. The algorithm has two main parts. First one is for partitioning the MANET into sub-networks, named &ldquo / clustering&rdquo / . Second part is composed of an efficient discovery of services on overall network. Clustering algorithm used in this study is enhanced version of DMAC (Distributed Mobility Adaptive Clustering, which is one of the golden algorithms of the wireless network clustering area). To be fast and flexible in service discovery layer, a simple and fastresponding algorithm is implemented. Integration of two algorithms enables devices to be mobile in the network

Current home networks typically involve two or more machines sharing network resources. The vision for the home network has grown from a simple computer network, to every day appliances embedded with network capabilities. In this environment devices and services within the home can interoperate, regardless of protocol or platform. Network clients can discover required resources by performing network discovery over component descriptions. Common approaches to this discovery process involve simple matching of keywords or attribute/value pairings. Interest emerging from the Semantic Web community has led to ontology languages being applied to network domains, providing a logical and semantically rich approach to both describing and discovering network components. In much of the existing work within this domain, developers have focused on defining new description frameworks in isolation from existing protocol frameworks and vocabularies. This work proposes an ontology-based description framework which takes the ontology approach to the next step, where existing description frameworks are in- corporated into the ontology-based framework, allowing discovery mechanisms to cover multiple existing domains. In this manner, existing protocols and networking approaches can participate in semantically-rich discovery processes. This framework also includes a system architecture developed for the purpose of reconciling existing home network solutions with the ontology-based discovery process. This work also describes an implementation of the approach and is deployed within a home-network environment. This implementation involves existing home networking frameworks, protocols and components, allowing the claims of this work to be examined and evaluated from a ‘real-world’ perspective.

Increasing number of software vendors are offering or planning to offer their applications as a Software-as-a-Service (SaaS) to leverage the benefits of cloud computing and Internet-based delivery. Therefore, potential clients will face increasing number of providers that satisfy their requirements to choose from. Consequently, there is an increasing demand for automating such a time-consuming and error-prone task. In this work, we develop an architecture for automated service discovery and selection in cloud computing environment. The system is based on an algorithm that recommends service choices to users based on both functional and non-functional characteristics of available services. The system also derives automated ratings from monitoring results of past service invocations to objectively detect badly-behaving providers. We demonstrate the effectiveness of our approach using an early prototype that was developed following object-oriented methodology and implemented using various open-source Java technologies and frameworks. The prototype uses a Chord DHT as its distributed backing store to achieve scalability.

Grids are collaborative distributed Internet systems characterized by large scale, heterogeneity, lack of central control, multiple autonomous administrative domains, unreliable components and frequent dynamic change. In such systems, it is desirable to maintain and query dynamic and timely information about active participants such as services, resources and user communities. The web services vision promises that programs are made more flexible, adaptive and powerful by querying Internet databases (registries) at runtime in order to discover information and network attached building blocks, enabling the assembly of distributed higher-level components. In support of this vision, we introduce the Web Service Discovery Architecture (WSDA), we introduce the hyper registry, which is a centralized database node for discovery of dynamic distributed content. It supports XQueries over a tuple set from a dynamic XML data model.

We are rapidly entering a world with an immense amount of services and devices available to humans and machines. This is a promising future, however there are at least two major challenges for using these services and devices: (1) they have to be found and (2) after being found, they have to be selected amongst. A significant difficulty lies in not only finding most available services, but presenting the most useful ones. In most cases, there may be too many found services and devices to select from. Service discovery needs to become more aimed towards humans and less towards machines. The service discovery challenge is especially prevalent in ubiquitous computing. In particular, service and device flux, human overloading, and service relevance are crucial. This thesis addresses the quality of use of services and devices, by introducing a sophisticated discovery model through the use of new layers in service discovery. This model allows use of services and devices when current automated service discovery and selection would be impractical by providing service suggestions based on user activities, domain knowledge, and world knowledge. To explore what happens when such a system is in place, a wizard of oz study was conducted in a command and control setting. To address service discovery in ubiquitous computing new layers and a test platform were developed together with a method for developing and evaluating service discovery systems. The first layer, which we call the Enhanced Traditional Layer (ETL), was studied by developing the ODEN system and including the ETL within it. ODEN extends the traditional, technical service discovery layer by introducing ontology-based semantics and reasoning engines. The second layer, the Relevant Service Discovery Layer, was explored by incorporating it into the MAGUBI system. MAGUBI addresses the human aspects in the challenge of relevant service discovery by employing common-sense models of user activities, domain knowledge, and world knowledge in combination with rule engines.  The RESPONSORIA system provides a web-based evaluation platform with a desktop look and feel. This system explores service discovery in a service-oriented architecture setting. RESPONSORIA addresses a command and control scenario for rescue services where multiple actors and organizations work together at a municipal level. RESPONSORIA was the basis for the wizard of oz evaluation employing rescue services professionals. The result highlighted the importance of service naming and presentation to the user. Furthermore, there is disagreement among users regarding the optimal service recommendation, but the results indicated that good recommendations are valuable and the system can be seen as a partner. / Vi rör oss snabbt in i en värld med en enorm mängd tjänster och enheter som finns tillgängliga för människor och maskiner. Detta är en lovande framtid, men det finns åtminstone två stora utmaningar för att använda dessa tjänster och enheter: (1) de måste hittas och (2) rätt tjänst/enhet måste väljas. En betydande svårighet ligger i att, inte bara finna de mest lättillgängliga tjänsterna och enheterna, men också att presentera de mest användbara sådana. I de flesta fall kan det vara för många tjänster och enheter som hittas för att kunna välja mellan. Upptäckten av tjänster och enheter behöver bli mer anpassad till människor och mindre till maskiner. Denna utmaning är särskilt framträdande i desktopmetaforens efterföljare Ubiquitous Computing. (Det vill säga en form av interaktion med datorer som blivit integrerad i aktiviteter och objekt i omgivningen.) Framförallt tjänster och enheters uppdykande och försvinnande, mänsklig överbelastning och tjänstens relevans är avgörande utmaningar. Denna avhandling behandlar kvaliteten på användningen av tjänster och enheter, genom att införa en sofistikerad upptäcktsmodell med hjälp av nya lager i tjänsteupptäcktsprocessen. Denna modell tillåter användning av tjänster och enheter när nuvarande upptäcktsprocess och urval av dessa skulle vara opraktiskt, genom att ge förslag baserat på användarnas aktiviteter, domänkunskap och omvärldskunskap. För att utforska vad som händer när ett sådant system är på plats, gjordes ett så kallat Wizard of Oz experiment i ledningscentralen på en brandstation. (Ett Wizard Of Oz experiment är ett experiment där användaren tror att de interagerar med en dator, men i själva verket är det en människa som agerar dator.) För att hantera tjänste- och enhetsupptäckt i Ubiquitous Computing utvecklades nya lager och en testplattform tillsammans med en metod för att utveckla och utvärdera system för tjänste- och enhetsupptäckt. Det första lagret, som vi kallar Förbättrat Traditionellt Lager (FTL), studerades genom att utveckla ODEN och inkludera FTL i den. ODEN utökar det traditionella, datororienterade tjänste- och enhetsupptäcktslagret genom att införa en ontologibaserad semantik och en logisk regelmotor. Det andra skiktet, som vi kallar Relevant Tjänst Lager, undersöktes genom att införliva det i systemet MAGUBI. MAGUBI tar sig an de mänskliga aspekterna i den utmaning som vi benämner relevant tjänste- och enhetsupptäckt, genom att använda modeller av användarnas aktiviteter, domänkunskap och kunskap om världen i kombination med regelmotorer. RESPONSORIA är en webbaserad plattform med desktoputseende och desktopkänsla, och är ett system för utvärdering av ovanstående utmaning tillsammans med de tidigare systemen. Detta system utforskar tjänste- och enhetsupptäckt i ett tjänsteorienterat scenario. RESPONSORIA tar ett ledningsscenario för räddningstjänst där flera aktörer och organisationer arbetar tillsammans på en kommunal nivå. RESPONSORIA låg till grund för ett Wizard of Oz experiment där experimentdeltagarna var professionella räddningsledare. Resultatet underströk vikten av namngivning av tjänster och enheter samt hur dessa presenteras för användaren. Dessutom finns det oenighet bland användare om vad som är den optimala service-/enhets-rekommendationen, men resultaten visar att goda rekommendationer är värdefulla och systemet kan ses som en partner.

With the advent of Service Oriented Architecture, Web Services have gained tremendous popularity. Due to the availability of a large number of Web services, finding an appropriate Web service according to the requirement of the user is a challenge. This warrants the need to establish an effective and reliable process of Web service discovery. A considerable body of research has emerged to develop methods to improve the accuracy of Web service discovery to match the best service. The process of Web service discovery results in suggesting many individual services that partially fulfil the user’s interest. By considering the semantic relationships of words used in describing the services as well as the use of input and output parameters can lead to accurate Web service discovery. Appropriate linking of individual matched services should fully satisfy the requirements which the user is looking for. This research proposes to integrate a semantic model and a data mining technique to enhance the accuracy of Web service discovery. A novel three-phase Web service discovery methodology has been proposed. The first phase performs match-making to find semantically similar Web services for a user query. In order to perform semantic analysis on the content present in the Web service description language document, the support-based latent semantic kernel is constructed using an innovative concept of binning and merging on the large quantity of text documents covering diverse areas of domain of knowledge. The use of a generic latent semantic kernel constructed with a large number of terms helps to find the hidden meaning of the query terms which otherwise could not be found. Sometimes a single Web service is unable to fully satisfy the requirement of the user. In such cases, a composition of multiple inter-related Web services is presented to the user. The task of checking the possibility of linking multiple Web services is done in the second phase. Once the feasibility of linking Web services is checked, the objective is to provide the user with the best composition of Web services. In the link analysis phase, the Web services are modelled as nodes of a graph and an allpair shortest-path algorithm is applied to find the optimum path at the minimum cost for traversal. The third phase which is the system integration, integrates the results from the preceding two phases by using an original fusion algorithm in the fusion engine. Finally, the recommendation engine which is an integral part of the system integration phase makes the final recommendations including individual and composite Web services to the user. In order to evaluate the performance of the proposed method, extensive experimentation has been performed. Results of the proposed support-based semantic kernel method of Web service discovery are compared with the results of the standard keyword-based information-retrieval method and a clustering-based machine-learning method of Web service discovery. The proposed method outperforms both information-retrieval and machine-learning based methods. Experimental results and statistical analysis also show that the best Web services compositions are obtained by considering 10 to 15 Web services that are found in phase-I for linking. Empirical results also ascertain that the fusion engine boosts the accuracy of Web service discovery by combining the inputs from both the semantic analysis (phase-I) and the link analysis (phase-II) in a systematic fashion. Overall, the accuracy of Web service discovery with the proposed method shows a significant improvement over traditional discovery methods.

Current technology for locating and validating composite services are not sufficient due to the following reasons. • Current frameworks do not have the capacity to create complete service descriptions since they do not model all the functional aspects together (i.e. the purpose of a service, state transitions, data transformations). Those that deal with behavioural descriptions are unable to model the ordering constraints between concurrent interactions completely since they do not consider the time taken by interactions. Furthermore, there is no mechanism to assess the correctness of a functional description. • Existing semantic-based matching techniques cannot locate services that conform to global constraints. Semantic-based techniques use ontological relationships to perform mappings between the terms in service descriptions and user requests. Therefore, unlike techniques that perform either direct string matching or schema matching, semantic-based approaches can match descriptions created with different terminologies and achieve a higher recall. Global constraints relate to restrictions on values of two or more attributes of multiple constituent services. • Current techniques that generate and validate global communication models of composite services yield inaccurate results (i.e. detect phantom deadlocks or ignore actual deadlocks) since they either (i) do not support all types of interactions (i.e. only send and receive, not service and invoke) or (ii) do not consider the time taken by interactions. This thesis presents novel ideas to deal with the stated limitations. First, we propose two formalisms (WS-ALUE and WS-π-calculus) for creating functional and behavioural descriptions respectively. WS-ALUE extends the Description Logic language ALUE with some new predicates and models all the functional aspects together. WS-π-calculus extends π-calculus with Interval Time Logic (ITL) axioms. ITL axioms accurately model temporal relationships between concurrent interactions. A technique comparing a WS-π-calculus description of a service against its WS-ALUE description is introduced to detect any errors that are not equally reflected in both descriptions. We propose novel semantic-based matching techniques to locate composite services that conform to global constraints. These constraints are of two types: strictly dependent or independent. A constraint is of the former type if the values that should be assigned to all the remaining restricted attributes can be uniquely determined once a value is assigned to one. Any global constraint that is not strictly dependent is independent. A complete and correct technique that locates services that conform to strictly dependent constraints in polynomial time, is defined using a three-dimensional data cube. The proposed approach that deals with independent constraints is correct, but not complete, and is a heuristic approach. It incorporates user defined objective functions, greedy algorithms and domain rules to locate conforming services. We propose a new approach to generate global communication models (of composite services) that are free of deadlocks and synchronisation conflicts. This approach is an extension of a transitive temporal reasoning mechanism.

Les systèmes autonomes sont des objets mobiles communicants capables de réaliser un certain nombre de tâches sans intervention humaine. Le coût (e.g. argent, poids, énergie) de la charge utile requise pour effectuer certaines missions est parfois trop important pour permettre aux engins d’embarquer la totalité des capacités nécessaires (i.e. capteurs et actionneurs). Répartir ces capacités sur plusieurs entités est une solution naturelle à ce problème. Un tel groupe d’entités constitue une flotte à laquelle il devient nécessaire de fournir un mécanisme de découverte permettant aux différents engins de partager leurs capacités respectives afin de résoudre une mission globale de façon collaborative. Ce mécanisme, outre l’affectation des tâches, doit gérer les conflits et les pannes potentielles qui peuvent survenir à tout moment sur tout engin de la flotte. Fort de ces constations, nous proposons un nouveau mécanisme collaboratif nommé AMiRALE qui apporte une solution aux problèmes ci-dessus pour les flottes hétérogènes d’engins mobiles autonomes. Notre système est entièrement distribué et repose uniquement sur des communications asynchrones. Nous proposonségalement un nouvel outil nommé NEmu permettant de créer des réseaux virtuels mobiles avec un contrôle important sur les propriétés de la topologie du réseau ainsi que sur la configuration des noeuds et des inter-connexions. Cet outil permet la réalisation d’expérimentations réalistes sur des prototypes d’applications réseaux. Enfin, nous proposons une évaluation de notre système collaboratif AMiRALE au travers d’un scénario de nettoyage de parc utilisant une flotte autonome de drones et de robots terrestres spécialisés. / We call autonomous systems, mobile and communicating objects which are able to perform several tasks without any human intervention. The overall cost (including price, weight and energy) of the payload required by some missions is sometimes too important to enable the entities to embed all the required capabilities (i.e. sensors and actuators). This is the reason why it is more suitable to spread all the capabilities among several entities. The team formed by those entities is called a swarm. It then becomes necessary to provide a discovery mechanism built into the swarm in order to enable its members to share their capabilities and to collaborate for achieving a global mission.This mechanism should perform task allocation as well as management of conflicts and failures which can occur at any moment on any entity of the swarm. In this thesis, we present a novel collaborative system which is called AMiRALE for heterogeneous swarms of autonomous mobile robots. Our system is fully distributed and relies only on asynchronous communications. We also present a novel tool called NEmu which enables to create virtual mobile networks with a complete control over the network topology, links and nodes properties. This tool is designed for performingrealistic experimentation on prototypes of network applications. Finally, we present experimental results on our collaborative system AMiRALE obtained through a park cleaning scenario which relies on an autonomous swarm of drones and specialized ground robots.