Sohail Jabbar

Dynamic clustering and management of mobile wireless sensor networks

In Wireless Sensor Networks (WSNs), routing data towards the sink leads to unbalanced energy consumption among intermediate nodes resulting in high data loss rate. The use of multiple Mobile Data Collectors (MDCs) has been proposed in the literature to mitigate such problems. MDCs help to achieve uniform energy-consumption across the network, fill coverage gaps, and reduce end-to-end communication delays, amongst others. However, mechanisms to support MDCs such as location advertisement and route maintenance introduce significant overhead in terms of energy consumption and packet delays. In this paper, we propose a self-organizing and adaptive Dynamic Clustering (DCMDC) solution to maintain MDC-relay networks. This solution is based on dividing the network into well-delimited clusters called Service Zones (SZs). Localizing mobility management traffic to a SZ reduces signaling overhead, route setup delay and bandwidth utilization. Network clustering also helps to achieve scalability and load balancing. Smaller network clusters make buffer overflows and energy depletion less of a problem. These performance gains are expected to support achieving higher information completeness and availability as well as maximizing the network lifetime. Moreover, maintaining continuous connectivity between the MDC and sensor nodes increases information availability and validity. Performance experiments show that DCMDC outperforms its rival in the literature. Besides the improved quality of information, the proposed approach improves the packet delivery ratio by up to 10%, end-to-end delay by up to 15%, energy consumption by up to 53%, energy balancing by up to 51%, and prolongs the network lifetime by up to53%.

Big-data: transformation from heterogeneous data to semantically-enriched simplified data

In big data, data originates from many distributed and different sources in the shape of audio, video, text and sound on the bases of real time; which makes it massive and complex for traditional systems to handle. For this, data representation is required in the form of semantically-enriched for better utilization but keeping it simplified is essential. Such a representation is possible by using Resource Description Framework (RDF) introduced by World Wide Web Consortium (W3C). Bringing and transforming data from different sources in different formats into the RDF form having rapid ratio of increase is still an issue. This requires improvements to cover transition of information among all applications with induction of simplicity to reduce complexities of prominently storing data. With the improvements induced in the shape of big data representation for transformation of data to form into Extensible Markup Language (XML) and then into RDF triple as linked in real time. It is highly needed to make transformation more data friendly. We have worked on this study on developing a process which translates data in a way without any type of information loss. This requires to manage data and metadata in such a way so they may not improve complexity and keep the strong linkage among them. Metadata is being kept generalized to keep it more useful than being dedicated to specific types of data source. Which includes a model explaining its functionality and corresponding algorithms focusing how it gets implemented. A case study is used to show transformation of relational database textual data into RDF, and at end results are being discussed.

Trust model at service layer of cloud computing for educational institutes

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.

Multilayer cluster designing algorithm for lifetime improvement of wireless sensor networks

Cluster-based network is a proven architecture for energy-aware routing, but more attention is required to ameliorate the energy consumption aspect of its cluster designing process. In this research work, we introduce a novel design of clustered network architecture. The proposed design technique is innovative in its idea. The general trend in this scene is either centralized decision at base station for cluster head selection and its members or distributed decision by exchanging information between neighboring nodes until the cluster head and its members are selected. Both the techniques drastically create mess in energy consumption due to too much broadcasting, especially in large networks as well as message exchange until some final decision is made. Our novel layer-based hybrid algorithm for cluster head and cluster member selection comes up to novel communication architecture. Since its substantial constituent is cluster designing, we named it Multilayer Cluster Designing Algorithm (MCDA). The proposed design not only has effect on lessening blind broadcasting, but also on decreasing the message exchange in a passionate way. It also encapsulates the beauty of efficient centralized decision making for cluster designing and energy-aware distributed cluster head selection and cluster member allocation process. Comprehensive experimentations have been performed on the comparative analysis of MCDA with state-of-the-art centralized and distributed cluster designing approaches present in published literature. Calculation of energy consumption in various operational parametric values, number of clusters designed and the number of packets broadcasted during cluster designing are the main performance evaluation parameters. It has been found that MCDA outperforms compared to its three competing algorithms with respect to the aforementioned parameters due to its multilayered synergistic mating approach.

Semantic Interoperability in Heterogeneous IoT Infrastructure for Healthcare

Interoperability remains a significant burden to the developers of Internet of Things’ Systems. This is due to the fact that the IoT devices are highly heterogeneous in terms of underlying communication protocols, data formats, and technologies. Secondly due to lack of worldwide acceptable standards, interoperability tools remain limited. In this paper, we proposed an IoT based Semantic Interoperability Model (IoT-SIM) to provide Semantic Interoperability among heterogeneous IoT devices in healthcare domain. Physicians communicate their patients with heterogeneous IoT devices to monitor their current health status. Information between physician and patient is semantically annotated and communicated in a meaningful way. A lightweight model for semantic annotation of data using heterogeneous devices in IoT is proposed to provide annotations for data. Resource Description Framework (RDF) is a semantic web framework that is used to relate things using triples to make it semantically meaningful. RDF annotated patients’ data has made it semantically interoperable. SPARQL query is used to extract records from RDF graph. For simulation of system, we used Tableau, Gruff-6.2.0, and Mysql tools.

Context-aware low power intelligent SmartHome based on the Internet of things

Constructing a smart home is not a task without intricate challenges due to involvement of various tools and technologies. Therefore, this research work presents a concept of context-aware low power intelligent SmartHome (CLPiSmartHome). For CLPiSmartHome, we propose a communication model, which provides a common medium for communication, i.e., same communication language. Moreover, an architecture is also proposed that welcomes all the electronic devices to communicate with each other using a single platform service. The proposed architecture describes the application, analysis and visualization aspects of the CLPiSmartHome. Furthermore, the feasibility and efficiency of the proposed system are implemented on Hadoop single node setup on UBUNTU 14.04 LTS coreTMi5 machine with 3.2GHz processor and 4 GB memory. Sample medical sensory data sets and fire detection datasets are tested on the proposed system. Finally, the results show that the proposed system architecture efficiently processes, analyzes, and integrates different datasets and triggers actions to provide safety measurements for elderly age people, patients, and others.

Mobility Aware Energy Efficient Congestion Control in Mobile Wireless Sensor Network

In this paper, we introduce a mobility aware and energy efficient congestion control protocol “time sharing energy efficient congestion control (TSEEC) for mobile wireless sensor network.” TSEEC is based on hybrid scheme of time division multiple access protocol (TDMA) and statistical time division multiple access (STDMA) protocol that inform the sensor nodes when to wake up and to go to listening state so as to save energy. This management helps in minimizing congestion and improving network energy conservation through its load based allocation (LBA) and time allocation leister (TAL) techniques. LBA is typically based on STDMA that uses sensor node information for assignment of dynamic timeslots to the sensor, nodes, whereas TAL targets the mobility management of sensor nodes that further comprises three main strategies of cluster member node that is, joining cluster, leaving cluster, and absence of data/redundant data with extricated time allocation (ETA), shift back time allocation (SBTA), and eScaped Time Allocation (STA) subtechniques. In addition, TSEEC protocol introduces the mobility pattern to control the mobile sensor node (MSN) movement to enable the protocol to effectively adapt itself to change the traffic environments and mobility. Mathematical analysis and NS2 simulation show that TSEEC outperforms SMAC in terms of energy consumption and packet deliver ratio. Furthermore, a comparative analysis of TSEEC with various well-known related MAC protocols is also given.

Energy efficient strategy for throughput improvement in wireless sensor networks.

Network lifetime and throughput are one of the prime concerns while designing routing protocols for wireless sensor networks (WSNs). However, most of the existing schemes are either geared towards prolonging network lifetime or improving throughput. This paper presents an energy efficient routing scheme for throughput improvement in WSN. The proposed scheme exploits multilayer cluster design for energy efficient forwarding node selection, cluster heads rotation and both inter- and intra-cluster routing. To improve throughput, we rotate the role of cluster head among various nodes based on two threshold levels which reduces the number of dropped packets. We conducted simulations in the NS2 simulator to validate the performance of the proposed scheme. Simulation results demonstrate the performance efficiency of the proposed scheme in terms of various metrics compared to similar approaches published in the literature.

E-MCDA: extended-multilayer cluster designing algorithm for network lifetime improvement of homogenous wireless sensor networks

The proposed idea in this paper is the constructive ramification of cluster designing mechanism floated in recently published work, multilayer cluster designing algorithm (MCDA) to ameliorate the performance in network lifetime. Novel algorithms for time slot allocation, minimizing the cluster head completion candidates, and cluster member selection∖node affiliation to cluster head play underpinning roles to achieve the target. These incorporations in MCDA result in minimizing transmissions, suppressing unfavorable response of transmissions and near-equal size and equal load clusters. We have done extensive simulations in NS2 and evaluate the performance of E-MCDA in energy consumption at various aspects of energy, packets transmission, number of designed clusters, number of nodes per cluster, and unclustered nodes. It is found that the proposed mechanism optimistically outperforms the competition with MCD and EADUC.

A REST-based industrial web of things’ framework for smart warehousing

A Web-oriented architecture using REST framework is proposed to enable warehouse objects to communicate over the Web. In the proposed mechanism, the smart warehouse consists of a data collection module and an administrative module. The former includes a collection of radio-frequency identification sensors to read RFID tags of the products, wireless sensors for operational data collection, and the actuators. It is responsible for the data collection process of products and goods stored in the warehouse as well as the collection of operational parameters, i.e. temperature, humidity, air quality, and pressure. The latter acts as the brain of the smart warehouse by processing data, organizing data, generating events, and executing actions. The warehouse user is provided with the environment to control the functionality of various sensors, things, appliances, and HAVC system of warehouse through the Web. An event decision system is built on top of the Web architecture to control real-time processing of the sensors, things, etc. In the proposed architecture, the smart gateway consists of two layers, namely transport module (TM) and device service module (DSM). The combination of TM and DSM creates the device controller for embedded devices operating on proprietary protocols. The proposed system is simulated and evaluated in various scenarios in context of discovery time, response time, and transmission failure. Its effect is seen in the form of improved performance of warehouse in quick interaction and in high accuracy as well.