Distance-Based and Low Energy Adaptive Clustering Protocol for Wireless Sensor Networks

A wireless sensor network (WSN) comprises small sensor nodes with limited energy capabilities. The power constraints of WSNs necessitate efficient energy utilization to extend the overall network lifetime of these networks. We propose a distance-based and low-energy adaptive clustering (DISCPLN) protocol to streamline the green issue of efficient energy utilization in WSNs. We also enhance our proposed protocol into the multi-hop-DISCPLN protocol to increase the lifetime of the network in terms of high throughput with minimum delay time and packet loss. We also propose the mobile-DISCPLN protocol to maintain the stability of the network. The modelling and comparison of these protocols with their corresponding benchmarks exhibit promising results

Internet of Things in Agricultural Innovation and Security

The agricultural Internet of Things (Ag-IoT) paradigm has tremendous potential in transparent integration of underground soil sensing, farm machinery, and sensor-guided irrigation systems with the complex social network of growers, agronomists, crop consultants, and advisors. The aim of the IoT in agricultural innovation and security chapter is to present agricultural IoT research and paradigm to promote sustainable production of safe, healthy, and profitable crop and animal agricultural products. This chapter covers the IoT platform to test optimized management strategies, engage farmer and industry groups, and investigate new and traditional technology drivers that will enhance resilience of the farmers to the socio-environmental changes. A review of state-of-the-art communication architectures and underlying sensing technologies and communication mechanisms is presented with coverage of recent advances in the theory and applications of wireless underground communications. Major challenges in Ag-IoT design and implementation are also discussed

Affinity-aware modeling of CPU usage with communicating virtual machines

Use of virtualization in Infrastructure as a Service (IaaS) environments provides benefits to both users and providers: users can make use of resources following a pay-per-use model and negotiate performance guarantees, whereas providers can provide quick, scalable and hardware-fault tolerant service and also utilize resources efficiently and economically. With increased acceptance of virtualization-based systems, an important issue is that of virtual machine migration-enabled consolidation and dynamic resource provisioning. Effective resource provisioning can result in higher gains for users and providers alike. Most hosted applications (for example, web services) are multi-tiered and can benefit from their various tiers being hosted on different virtual machines. These mutually communicating virtual machines may get colocated on the same physical machine or placed on different machines, as part of consolidation and flexible provisioning strategies. In this work, we argue the need for network affinity-awareness in resource provisioning for virtual machines. First, we empirically quantify the change in CPU resource usage due to colocation or dispersion of communicating virtual machines for both Xen and KVM virtualization technologies. Next, we build models based on these empirical measurement to predict the change in CPU utilization when transitioning between colocated and dispersed placements. Due to the modeling process being independent of virtualization technology and specific applications, the resultant model is generic and application-agnostic. Via extensive experimentation, we evaluate the applicability of our models for synthetic and benchmark application workloads. We find that the models have high prediction accuracy maximum prediction error within 2% absolute CPU usage. (C) 2013 Elsevier Inc. All rights reserved