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This book analyses the US drone attacks against terrorists in Pakistan to assess whether the pre-emptive' use of combat drones to kill terrorists is ever legally justified. Exploring the doctrinal discourse of pre-emption vis--vis the US drone attacks against terrorists in Pakistan, the book shows that the debate surrounding this discourse encapsulates crucial tensions between the permission and limits of the right of self-defence. Drawing from the long history of God-given and man-made laws of war, this book employs positivism as a legal frame to explore and explain the doctrine of pre-emption and analyses the doctrine of the state's rights to self-defence as it stretches into pre-emptive or preventive use of force. The book investigates why the US chose the recourse to pre-emption through the use of combat drones in the war on terror' and whether there is a potential future for the pre-emption of terrorism through combat drones. The author argues that the policy to kill first' is easy to adopt; however, any disregard for the web of legal requirements surrounding the policy has the potential to undercut the legal claims of an armed act. The book enables the framing and analysis of such controversies in legal terms as opposed to a choice between law and policy. An examination of the legal dilemma concerning drone warfare, this book will be of interest to academics in the fields of international relations, Asian politics, South Asian studies, and security studies, in particular, global security law, new wars, and emerging technologies of warfare.

Underwater Wireless Sensor Networks (UWSNs) are an enabling technology for many applications in commercial, military, and scientific domains. In some emergency response applications of UWSN, data dissemination is more important, therefore these applications are handled differently as compared to energy-focused approaches, which is only possible when propagation delay is minimized and packet delivery at surface sinks is assured. Packet delivery underwater is a serious concern because of harsh underwater environments and the dense deployment of nodes, which causes collisions and packet loss. Resultantly, re-transmission causes energy loss and increases end-to-end delay ([Formula: see text]). In this work, we devise a framework for the joint optimization of sink mobility, hold and forward mechanisms, adoptive depth threshold ([Formula: see text]) and data aggregation with pattern matching for reducing nodal propagation delay, maximizing throughput, improving network lifetime, and minimizing energy consumption. To evaluate our technique, we simulate the three-dimensional (3-D) underwater network environment with mobile sink and dense deployments of sensor nodes with varying communication radii. We carry out scalability analysis of the proposed framework in terms of network lifetime, throughput, and packet drop. We also compare our framework to existing techniques, i.e., Mobicast and iAMCTD protocols. We note that adapting varying [Formula: see text] based on node density in a range of network deployment scenarios results in a reduced number of re-transmissions, good energy conservation, and enhanced throughput. Furthermore, results from extensive simulations show that our proposed framework achieves better performance over existing approaches for real-time delay-intolerant applications.