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We modeled the mobility of mobile phone users in order to study the fundamental spreading patterns that characterize a mobile virus outbreak. We find that although Bluetooth viruses can reach all susceptible handsets with time, they spread slowly because of human mobility, offering ample opportunities to deploy antiviral software. In contrast, viruses using multimedia messaging services could infect all users in hours, but currently a phase transition on the underlying call graph limits them to only a small fraction of the susceptible users. These results explain the lack of a major mobile virus breakout so far and predict that once a mobile operating system's market share reaches the phase transition point, viruses will pose a serious threat to mobile communications.

Over the last couple of decades, clustering-based protocols are believed to be the best for heterogeneous wireless sensor networks (WSNs) because they work on the principle of divide and conquer. In this study, the authors propose and evaluate two new clustering-based protocols for heterogeneous WSNs, which are called single-hop energy-efficient clustering protocol (S-EECP) and multi-hop energy-efficient clustering protocol (M-EECP). In S-EECP, the cluster heads (CHs) are elected by a weighted probability based on the ratio between residual energy of each node and average energy of the network. The nodes with high initial energy and residual energy will have more chances to be elected as CHs than nodes with low energy whereas in M-EECP, the elected CHs communicate the data packets to the base station via multi-hop communication approach. To analyse the lifetime of the network, the authors assume three types of sensor nodes equipped with different battery energy. Finally, simulation results indicate that the authors protocols prolong network lifetime, and achieve load balance among the CHs better than the existing clustering protocols.

The localisation of moving and transceiver-free objects is addressed by processing the Received Signal Strength Indicator (RSSI) available at the nodes of a wireless sensor network. Starting from the RSSI measurements, the probability of the presence of unknown mobile objects is determined by means of a customised classification approach based on a support vector machine. Experimental results assess the feasibility of the proposed approach.

An efficient rectenna based on a dual Schottky diodes converter has been designed at 2.45 GHz. The proposed rectifying circuit is well suitable for wireless sensor applications because no input lowpass filter and no via-hole connections are required, resulting in a more simple structure. A simulation mixing an electromagnetic and circuit analysis has been first used to optimise the rectifier. In addition, the performances of the rectenna has been correctly predicted and characterised using an FDTD formulation extended to lumped circuit elements. The realised rectenna exhibits 83% efficiency over a 1050 V resistive load at a power density of 0.31 mW/cm 2 .

Traditional routing protocols are no longer suitable for the energy harvesting-wireless sensor networks (EH-WSN), which is powered by the energy harvested from environment instead of batteries. Rather than minimising the energy consumption and maximising the network lifetime, the main challenge in EH-WSN is to maximise its working performance under energy harvesting constraints. In this study, the authors propose a centralised power efficient routing algorithm energy harvesting genetic-based unequal clustering-optimal adaptive performance routing algorithm (EHGUC-OAPR) which contains two parts: (i) energy harvesting genetic-based unequal clustering algorithm EHGUC and (ii) optimal adaptive performance routing algorithm (OAPR). First, the base station (BS) uses EHGUC algorithm to form clusters of unequal size and select associated cluster heads, in which the clusters closer to the BS have smaller size. Then, the BS adopts OAPR algorithm to construct an optimal routing among each cluster heads. The numerical results show that EHGUC-OAPR is not only well applied to EH-WSN, but also has a great improvement in network energy balance and data delivery ratio.

The problem of energy conservation in wireless image sensor networks is addressed, and a fast zonal discrete cosine transform (DCT) design which aims to decrease the complexity of JPEG baseline compression is presented. Energy consumption measurements have been made on a real wireless camera node in order to evaluate the amount of energy which can be saved during the image compression process without loss of visual quality. Although the gain depends on the compression rate, such a DCT design is a simple and effective way to prolong the lifetime of the camera nodes, and thereby the network lifetime.

A compact stacked implantable antenna for biotelemetry in medical implant communication services band (MICS band: 402-405MHz) is proposed. Using a stacked planar inverted-F antenna (PIFA) structure can enhance bandwidth and reduce the effect of frequency shift in human tissue giving complex and highly variable characteristics. The antenna looks like one dime (US currency) and has a 7.5mm radius, 1.9mm thickness, operating frequency at 402MHz and a bandwidth of 50MHz at return loss of 10dB. A miniature, broadband stacked implantable antenna for biotelemetry with medical devices is provided.

Underwater wireless sensor networks (UWSNs) have recently received a significant amount of attention. Since they have delay/disruption-tolerant networks (DTNs) characteristics, the design of any UWSN scheme must take DTN influences into account, especially in routing protocols. Many researchers have proposed various DTN routing techniques for different types of DTN routing schemes in UWSNs. The authors survey state-of-the-art DTN routing protocols, and use the definition of DTN to classify these proposals into scheduled contact, opportunistic contact and predicted contact. Furthermore, the authors analyse the detailed information in order to draw up a comparison table and also expect to inspire more research into this topic in the future.