Wireless Sensor Networks (WSNs) have revolutionized the era of conventional computing into a digitized world, commonly known as "The Internet of Things". WSN consists of tiny low-cost sensing devices, having computation, communication and sensing capabilities. These networks are always debatable for their limited resources and the most arguable and critical issue in WSNs is energy efficiency. Sensors utilize energy in broadcasting, routing, clustering, on-board calculations, localization, and maintenance, etc. However, primary domains of energy consumption at node level are three i.e. sensing by sensing-module, processing by microprocessor and communication by radio link. Extensive sensing, over-costs processing and frequent communication not only minimize the network lifetime , but also affects the availability of these resources for other tasks. To increase lifetime and provide an energy-efficient WSN, here we have proposed a new scheme called "A Content-based Adaptive and Dynamic Scheduling (CADS) using two ways communication model in WSNs". CADS dynamically changes a node states during data aggregation and each node adapts a new state based on contents of the sensed data packets. Analyzer module at the Base-Station investigates contents of sensed data packets and regulates functions of a node by transmitting control messages in a backward direction. CADS minimizes energy consumption by reducing unnecessary network traffic and avoid redundant message-forwarding. Simulation results have been shown that it increases energy-efficiency in terms of network lifetime by 9.65% in 100 nodes-network, 11.36% in 150 nodes-network and 0.94% in 300 nodes. The proposed scheme is also showing stability in terms of increasing cluster life by 87.5% for a network of 100 nodes, 94.73% for 150 nodes and 53.9% in 300 nodes.

Industrial Internet of Things (IIoT) is a new type of Internet of Things (IoT), which enables sensors to merge with several smart devices to monitor machine status, environment, and collect data from industrial devices. On the other hand, cloud computing provides a good platform for storing crowdsourced data of IIoT. Due to the semi-trusted nature of cloud computing and communication through open channels, the IIoT environment needs security services such as confidentiality and authenticity. One such solution is provided by the identity-based signcryption. Unfortunately, the identity-based signcryption approach suffers from the key escrow problem. Certificateless signcryption is the alternative of identity-based signcryption that can resolve the key escrow problem. Here, we propose a lightweight certificateless signcryption approach for crowdsourced IIoT applications with the intention of enhancing security and decreasing the computational cost and communication overhead. The security and efficiency of the proposed approach are based on the hyper elliptic curve cryptosystem. The hyper elliptic curve is the advance version of the elliptic curve having small parameters and key size of 80 bits as compared to the elliptic curve which has 160-bits key size. Further, we validate the security requirements of our approach through automated validation of Internet security protocols and applications (AVISPA) tool with the help of high level protocol specification language (HLPSL). Moreover, our lightweight and secured scheme will attract low resource devices and will become a perk in the environment of IIoT.

This study contributes to the extant literature on the nexus among agriculture export, import exchange rate and economic growth in Pakistan. We used annual time series data for 1980-2017 and employ the Non-linear Autoregressive Distributed Lag (NARDL) model. The NARDL testing results affirms asymmetric co-integration among the variables. The study main results show: (i) Co-integration test for long run the positive shocks in export and import have positive significant while exchange rate has positive effect the economic growth. (ii) Co-integration test for short run the positive shocks in import has positive significant and while Export and exchange rate have negative significant effect on economic growth. The symmetrical results show: (i) Export has unidirectional granger causality (ii) Exchange rate has bidirectional granger causality (iii) Import has not ganger causality with economic growth. In addition, the results demonstrated that causality relationship can help out policy maker to design such policies which are useful to economic growth of Pakistan, which could further promote foreign trade to gain the maximum level of economic growth.

This study contributes to the extant literature on the nexus among rice, maize and wheat production with agriculture gross domestic product (AGDP) of Pakistan. We use time series data from 1970 to 2017 and employ the Non-linear Autoregressive Distributed Lag (NARDL) model. Short run and long run shocks between the selected variables and result’s is checked through the co-integration and nonlinear error correction model.Autoregressive distributed lag bound testing approach for co-integration and to find the relationship between variables Granger causality test is applied.Our results confirm co-integration, positive shocks results show that rice, maize and wheat production have significantly influence on AGDP. The asymmetrically positive shocks of three crops have neutral effect on AGDP. While in symmetric results show the unidirectional effect between rice, maize production with AGDP and wheat production do not have ganger causality with AGDP. Finally, results depict that wheat, maize and rice production significantly contributes to agricultural GDP in the case of Pakistan.

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