An efficient algorithm for partially matched servi

Authors: Mariwan Ahmed Lu Liu James Hardy Bo Yuan Nick Antonopoulos

Publish Date: 2016/05/11

Volume: 20, Issue: 3, Pages: 283-293

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Abstract

Internet of Things IoT connects billions of devices in an Internetlike structure Each device encapsulated as a realworld service which provides functionality and exchanges information with other devices This largescale 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 realworld services showed that the proposed method achieved significant improvement in the accuracy and performance in the selection processWith the increasing popularity of Internet of Things IoT hardware becoming smaller cheaper and more powerful however majority of them have computation and communication capabilities which they use to connect interact and exchange information with surrounding environments 1 The proliferation of wireless systems such as Bluetooth Radio Frequency Identification RFID WiFi telephone data services embedded sensors and actuator nodes has allowed the IoT to develop from infancy and it is on the verge to transform current static internet to a fully integrated Future Internet 2 The interaction between all these devices will lead to a large amount of data which needs storing processing analysing and presenting in an efficient convenient and useable format In the IoT environment dynamic network query discovery selection and ondemand provisioning of services are of crucial importanceOne application area of IoT is the emergency and accident management services The number of emergency cases increases with increasing population and increasing hazard potential from eg the number of cars on the roads According to Health and Social Care Information Centre HSCIC 3 the number of accident and emergency attendances in England for 2012–2013 is more than 183 million To provide the most suitable service for emergency cases and achieve better performance Emergency Management Services can provide a unified platform to connect all local and private sector emergency command centres Concurrently wireless sensor networks can be used for surveillance and precise automated data collection regarding the emergency case and required servicesThere are varieties of attributes which determine the type of emergency service available for a given case The data are generally dynamic in nature such as crew members and therefore capabilities in particular vehicles on a particular shift While the majority of the data is dynamic the change rate is not synchronized For example some of the data are slowly changing eg vehicles owned by a county service some are moderately changing eg qualifications and capabilities of crew members and some is rapidly changing eg current location and status/availability To search for the most suitable service consideration needs to be given to the different service types fire police ambulance coast guard antiterrorist unit etc and then the attributes which would include vehicle type cycle motorcycle car transit vehicle aircraft vehicle capability four wheel drive number of seats number of beds vehicle equipment defibrillator oxygen breathing apparatus underwater search equipment access equipment personnel capability fully qualified/part qualified/undertaking training in eg resuscitation working at altitude crash investigation current service location current service availability owner of service provision county borough private etcDifferent consumers have different QoS requirements The diversity in many cases leads to partial matching in which we cannot find enough services which perfect match all the criteria An example could be for a motorway vehicle accident involving chemical transportation injuries vehicle instability hazardous materials volatile air supply chemical clean up distance to services etc In this example a service was not specified only a partial attribute list The search would need to be automated based on a reported incident and call handler recordingFor the emergency support service existing technologies in serviceoriented systems may be leveraged to provide partial solutions Within serviceoriented architecture SOA services are considered as selfcontained selfdescribing modular applications that can be published found and invoked across the web 4 SOA stores all the services in repositories those services can be selected and invoked automatically Therefore it can be suggested that it needs more effort to build a more accurate and efficient service selection method to overcome the challenges facing by the process of emergency support serviceIn this paper we propose an efficient and dynamic algorithm for selection of disaster services based on partial matching of service QoS attributes Furthermore an accurate ranking algorithm is provided by considering the deviation of QoS values from disaster nominal requirementsPartial matching—where the available emergency services do not fully match every QoS requirements The degree of partial matching is dependent on the number of recommended services the user needs In extreme circumstances this allows our algorithm to recommend the most suitable services instead of returning an empty list The selection algorithm should avoid excluding those partially matched disaster services

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