Refining Network Lifetime of Wireless Sensor Network Using Energy-Efficient Clustering and DRL-Based Sleep Scheduling.

This research article published by MDPI, 2020Over the recent era, Wireless Sensor Network (WSN) has attracted much attention among industrialists and researchers owing to its contribution to numerous applications including military, environmental monitoring and so on. However, reducing the network delay and improving the network lifetime are always big issues in the domain of WSN. To resolve these downsides, we propose an Energy-Efficient Scheduling using the Deep Reinforcement Learning (DRL) (ES-DRL) algorithm in WSN. ES-DRL contributes three phases to prolong network lifetime and to reduce network delay that is: the clustering phase, duty-cycling phase and routing phase. ES-DRL starts with the clustering phase where we reduce the energy consumption incurred during data aggregation. It is achieved through the Zone-based Clustering (ZbC) scheme. In the ZbC scheme, hybrid Particle Swarm Optimization (PSO) and Affinity Propagation (AP) algorithms are utilized. Duty cycling is adopted in the second phase by executing the DRL algorithm, from which, ES-DRL reduces the energy consumption of individual sensor nodes effectually. The transmission delay is mitigated in the third (routing) phase using Ant Colony Optimization (ACO) and the Firefly Algorithm (FFA). Our work is modeled in Network Simulator 3.26 (NS3). The results are valuable in provisions of upcoming metrics including network lifetime, energy consumption, throughput and delay. From this evaluation, it is proved that our ES-DRL reduces energy consumption, reduces delays by up to 40% and enhances throughput and network lifetime up to 35% compared to the existing cTDMA, DRA, LDC and iABC methods

Reinforcement based Cognitive Algorithms to Detect Malicious Node in Wireless Networks

The growth of wireless communication technologies and its applications leads to many security issues. Malicious node detection is one among the major security issues. Adoption of cognition can detect and Prevent malicious activities in the wireless networks. To achieve cognition into wireless networks, we are using reinforcement learning techniques. By using the existing reinforcement techniques, we have proposed GreedyQ cognitive (GQC) and SoftSARSA cognitive (SSC) algorithms for malicious node detection and the performances among these algorithms are evaluated and the result shows SSC algorithm is best algorithm. The proposed algorithms perform better in malicious node detection as compared to the existing algorithms

Adaptive Energy Saving and Mobility Support IPv6 Routing Protocol in Low-Power and Lossy Networks for Internet of Things and Wireless Sensor Networks

Internet of Things (IoT) is an interconnection of physical objects that can be controlled, monitored and exchange information from remote locations over the internet while been connected to an Application Programme Interface (API) and sensors. It utilizes low-powered digital radios for communication enabling millions and billions of Low-power and Lossy Network (LLN) devices to communicate efficiently via a predetermined routing protocol. Several research gaps have identified the constraints of standardised versions of IPv6 Routing Protocol for Low Power and Lossy Networks evidently showing its lack of ability to handle the growing application needs and challenges. This research aims to handle routing from a different perspective extending from energy efficiency, to mobility aware and energy scavenging nodes thereby presenting numerous improvements that can suit various network topologies and application needs. Envisioning all the prospects and innovative services associated with the futuristic ubiquitous communication of IoT applications, we propose an adaptive Objective Function for RPL protocol known as Optimum Reliable Objective Function (OR-OF) having a fuzzy combination of five routing metrics which are chosen based on system and application requirements. It is an approach which combines the three proposed implemented Objective Functions within this thesis to enable the OR-OF adapt to different routing requirements for different IoT applications. The three proposed OFs are Energy saving Routing OF, Enhanced Mobility Support Routing OF and Optimized OF for Energy Scavenging nodes. All proposed OFs were designed, implemented, and simulated in COOJA simulator of ContikiOS, and mathematical models were developed to validate simulated results. Performance Evaluation indicated an overall improvement as compared with the standardised versions of RPL protocols and other related research works in terms of network lifetime with an average of 40%, packet delivery ratio of 21%, energy consumption of 82% and End-to-End Delay of 92%

Proceedings of the Salford Postgraduate Annual Research Conference (SPARC) 2011

These proceedings bring together a selection of papers from the 2011 Salford Postgraduate Annual Research Conference(SPARC). It includes papers from PhD students in the arts and social sciences, business, computing, science and engineering, education, environment, built environment and health sciences. Contributions from Salford researchers are published here alongside papers from students at the Universities of Anglia Ruskin, Birmingham City, Chester,De Montfort, Exeter, Leeds, Liverpool, Liverpool John Moores and Manchester

On Counterinsurgency: Firepower, Biopower, and the Collateralization of Milliatry Violence

This dissertation investigates the most recent cycle of North Atlantic expeditionary warfare by addressing the resuscitation of counterinsurgency warfare with a specific focus on the war in Afghanistan from 2006 to 2014. The project interrogates the lasting aesthetic, epistemological, philosophical, and territorial implications of counterinsurgency, which should be understood as part of wider transformations in military affairs in relation to discourses of adaptation, complexity, and systemic design, and to the repertoire of global contingency and stability operations. Afghanistan served as a counterinsurgency laboratory, and the experiments will shape the conduct of future wars, domestic security practices, and the increasingly indistinct boundary between them. Using work from Michel Foucault and liberal war studies, the project undertakes a genealogy of contemporary population-centred counterinsurgency and interrogates how its conduct is constituted by and as a mixture firepower and biopower. Insofar as this mix employs force with different speeds, doses, and intensities, the dissertation argues that counterinsurgency unrestricts and collateralizes violence, which is emblematic of liberal war that kills selectively to secure and make life live in ways amenable to local and global imperatives of liberal rule. Contemporary military counterinsurgents, in conducting operations on the edges of liberal rule's jurisdiction and in recursively influencing the domestic spaces of North Atlantic states, fashion biopoweras custodial power to conduct the conduct of lifeto shape different interventions into the everyday lives of target populations. The 'lesser evil' logic of counterinsurgency is used to frame counterinsurgency as a type of warfare that is comparatively low-intensity and less harmful, and this justification actually lowers the threshold for violence by making increasingly indiscriminate the ways in which its employment damages and envelops populations and communities, thereby allowing counterinsurgents to speculate on the practice of expeditionary warfare and efforts to sustain occupations. Thus, the dissertation argues that counterinsurgency is a communicative process, better understood as mobile military media with an atmospheric-environmental register blending acute and ambient measures that are always-already kinetic. The counterinsurgent gaze enframes a world picture where everything can be a force amplifier and everywhere is a possible theatre of operations

The Cultural Landscape & Heritage Paradox; Protection and Development of the Dutch Archeological-Historical Landscape and its European Dimension

To what extent can we know past and mainly invisible landscapes, and how we can use this still hidden knowledge for actual sustainable management of landscape’s cultural and historical values. It has also been acknowledged that heritage management is increasingly about ‘the management of future change rather than simply protection’. This presents us with a paradox: to preserve our historic environment, we have to collaborate with those who wish to transform it and, in order to apply our expert knowledge, we have to make it suitable for policy and society. The answer presented by the Protection and Development of the Dutch Archaeological-Historical Landscape programme (pdl/bbo) is an integrative landscape approach which applies inter- and transdisciplinarity, establishing links between archaeological-historical heritage and planning, and between research and policy. This is supported by two unifying concepts: ‘biography of landscape’ and ‘action research’. This approach focuses upon the interaction between knowledge, policy and an imagination centered on the public. The European perspective makes us aware of the resourcefulness of the diversity of landscapes, of social and institutional structures, of various sorts of problems, approaches and ways forward. In addition, two related issues stand out: the management of knowledge creation for landscape research and management, and the prospects for the near future. Underlying them is the imperative that we learn from the past ‘through landscape’

Undergraduate Catalog 2008-2009

None published in 1960. Volume for 1975-76 issued in 2 parts: part 1. General information -- part 2. Curricula and courses. Supplement for 1961 entitled: Summer sessions, 1961. Continued in part by University of South Florida. Graduate School programs, [1985/86]- Continued by the CD-ROM publication: USF academic information.https://digitalcommons.usf.edu/usf_catalogs/1040/thumbnail.jp