Purav Shah

Write strategies for multiterabit per square inch scanned-probe phase-change memories

A mark-length write strategy for multiterabit per square inch scanned-probe memories is described that promises to increase the achievable user density by at least 50%, and potentially up to 100% or more, over conventional approaches. The viability of the write strategy has been demonstrated by experimental scanning probe write/read measurements on phase-change (GeSbTe) media. The advantages offered by adopting mark-length recording are likely to be equally applicable to other forms of scanned probe storage.

The Design of Rewritable Ultrahigh Density Scanning-Probe Phase-Change Memories

A systematic design of practicable media suitable for rewritable, ultrahigh density (>;1Tbit/sq.in.), high data rate (>;1Mbit/s/tip) scanning-probe phase-change memories is presented. The basic design requirements were met by a Si/TiN/Ge2Sb2Te5 (GST)/diamond-like carbon structure, with properly tailored electrical and thermal conductivities. Various alternatives for providing rewritability were investigated. In the first case, amorphous marks were written into a crystalline starting phase and subsequently erased by recrystallization, as in other already established phase-change memory technologies. Results imply that this approach is also appropriate for probe-based memories. However, experimentally, the successful writing of amorphous bits using scanning electrical probes has not been widely reported. In light of this, a second approach has been studied, that of writing crystalline bits in an amorphous starting matrix, with subsequent erasure by reamorphization. With conventional phase-change materials, such as continuous films of GST, this approach invariably leads to the formation of a crystalline “halo” surrounding the erased (reamorphized) region, with severe adverse consequences on the achievable density. Suppression of the “halo” was achieved using patterned media or slow-growth phase-change media, with the latter seemingly more viable.

Architecture for public safety network using D2D communication

Device to Device (D2D) communication has been proposed as an underlay to Long-Term evolution (LTE) network as a means of harvesting the proximity, reuse and hop gains. However, D2D communication can also serve as a technology for providing public safety and disaster relief services. In this article, the basic concepts of D2D communications are first introduced and then existing fundamental works on disaster communication are discussed. We focus on the performance of the network architecture by utilizing the relay assisted transmission which can effectively enhance the capacity and power saving of the network. We also propose the distance based strategy to reduce the computational complexity and power transmission. Finally, simulation results are provided to verify the proposed architecture.

A Hybrid Double-Threshold Based Cooperative Spectrum Sensing over Fading Channels

This paper investigates double-threshold-based energy detector for cooperative spectrum sensing mechanisms in cognitive wireless radio networks. We first propose a hybrid double-threshold-based energy detector (HDTED) to improve the sensing performance at secondary users (SUs) by exploiting both the local binary/energy decisions and global binary decisions feedback from the fusion center (FC). Significantly, we derive closed-form expressions and bounds for the probabilities of missed detection and false alarm considering a practical scenario where all channel links suffer from Rayleigh fading and background noise. The derived expressions not only show the improved performance achieved with the HDTED scheme but also enable us to analyze the impacts of the number of the SUs and the fading channels on the cooperative spectrum sensing performance. Furthermore, based on the derived bounds, we propose an optimal SU selection algorithm for forwarding the local decisions to the FC, which helps reduce the number of forwarding bits for a lower-complexity signaling. Finally, numerical results are provided to demonstrate the validity of the analytical findings.

Towards connecting people, locations and real-world events in a cellular network

CDRs containing voice-calls and SMS activities from a cellular network in Senegal.Large-scale CDR datasets collected over one year from randomly sampled customers.The study analyses the telecommunication traffic flows patterns.Exceptional spatio-temporal patterns are correlated to real-world events. The success of personal mobile communication technologies has led an emerging expansion of the telecommunication infrastructure but also to an explosion to mobile broadband data traffic as more and more people completely rely on their mobile devices, either for work or entertainment. The continuously interaction of their mobile devices with the mobile network infrastructure creates digital traces that can be easily logged by the network operators. These digital traces can be further used, apart from billing and resource management, for large-scale population monitoring using mobile traffic analysis. They could be integrated into intelligent systems that could help at detecting exceptional events such as riots, protests or even at disaster preventions with minimal costs and improve people safety and security, or even save lives. In this paper we study the use of fully anonymized and highly aggregate cellular network data, like Call Detail Records (CDRs) to analyze the telecommunication traffic and connect people, locations and events. The results show that by analyzing the CDR data exceptional spatio-temporal patterns of mobile data can be correlated to real-world events. For example, high user network activity was mapped to religious festivals, such as Ramadan, Le Grand Magal de Touba and the Tivaouane Maouloud festival. During the Ramadan period it was noticed that the communication pattern doubled during the night with a slow start during the morning and along the day. Furthermore, a peak increase in the number of voice calls and voice calls duration in the area of Kafoutine was mapped to the Casamance Conflict in the area which resulted in four deaths. Thus, these observations could be further used to develop an intelligent system that detects exceptional events in real-time from CDRs data monitoring. Such system could be used in intelligent transportation management, urban planning, emergency situations, network resource allocation and performance optimization, etc.

Exploring energy consumption issues for multimedia streaming in LTE HetNet Small Cells

Due to the ever growing mobile broadband data traffic over the cellular networks, the small cell deployment is seen as a promising solution for the network operators to increase their network capacity at low cost. This in turn would lead to an increase number of handovers (HOs) for the mobile users, which could affect the device power consumption. In this context, this paper investigates the impact of the HO process on the device energy consumption while performing VoD over a real LTE Small Cell experimental environment. Subjective tests are carried out to study the impact of the video quality on the user perceived QoE. The results show that by changing the quality level of the multimedia stream the energy can be greatly conserved while the user perceived QoE is still acceptable. Furthermore, by adapting to a lower quality level during the HO process, up to 56% energy savings could be achieved.

Disaster management communication networks: Challenges and architecture design

In the past decades, serious natural disasters such as earthquakes, tsunamis, floods, and storms have occurred frequently worldwide with catastrophic consequences. They also helped us understand that organising and maintaining effective communication during the disaster are vital for the execution of rescue operations. As communication resources are often entirely or partially damaged by disasters, the demand for information and communication technology (ICT) services explosively increases just after the events. These situations instigate serious network traffic congestions and physical damage of ICT equipments and emergency ICT networks if uprooted as a pre-disaster network system. This article proposes a network architecture design by integrating the existing network infrastructure with the reinforcement of layers based techniques and cloud processing concepts. This resilient network architecture allows the ICT services to be launched within a reasonable short period of time of development. Furthermore, communication in a disaster is sustained by implementing a three-tier fortification of the overall network architecture which would also minimize the physical and logical redundancy for resilient and flexible ICT resources. As cloud processing will work as a parallel reinforced infrastructure, the proposed approach and network design will give new hope for the developing countries to consider cloud computing services for effectiveness and better dependability on the architecture to save ICT and humanitarian network at the time of disaster.

Modelling Wireless Sensor Networks for Performability Evaluation

The higher demand for use of Wireless Sensor Technology, in the presence of complexities of various deployment environments, and application areas such as wireless multimedia sensor networks, call for the need to improve performance and availability of WSNs. This paper seeks to justify the need to model both performance and availability of WSNs together, parting from the current independent approaches and provides a systematic modelling approach for performability of WSNs. This has further been necessitated by positive research findings facilitating repair and replacement of faulty and dead sensor nodes and communication links. Two different analytical solution approaches are employed for performability modelling of a WSN cluster, and simulation results presented are in agreement with the analytical approximations.

Deployment Challenges and Developments in Wireless Sensor Networks Clustering

Clustering techniques for wireless sensor networks (WSNs) have been extensively studied and proven to improve the network lifetime, a primary metric, used for performance evaluation of sensor networks. Although introduction of clustering techniques has the potential to reduce energy consumption and extend the lifetime of the network by decreasing the contention through either power control or node scheduling, scalability remains an issue. Therefore, the optimality of the cluster size still needs to be thoroughly investigated. In this paper, a single cluster head (CH) queuing model is presented. Using an event based simulation tool (Castalia), key issues that affect the practical deployment of clustering techniques in wireless sensor networks are analysed. These include identifying the bottlenecks in terms of cluster scalability and predicting the nature of data packets arrival distribution at the CH. Results presented show that this analysis can be used to specify the size of a cluster, when a specific flow of data is expected from the sensing nodes based on a particular application and also the distribution of the inter-arrival times of data packets at the CH follows exponential distribution.

A novel low complexity Local Hybrid Pseudo-SSIM-SATD distortion metric towards perceptual rate control

The front-end block-based video encoder applies an Image Quality Assessment (IQA) as part of the distortion metric. Typically, the distortion metric applies uniform weighting for the absolute differences within a Sub-Macroblock (Sub-MB) at any given time. As video is predominately designed for Humans, the distortion metric should reflect the Human Visual System (HVS). Thus, a perceptual distortion metric (PDM), will lower the convex hull of the Rate-Distortion (R-D) curve towards the origin, by removing perceptual redundancy and retaining perceptual clues. Structured Similarity (SSIM), a perceptual IQA, has been adapted via logarithmic functions to measure distortion, however, it is restricted to the Group of Picture level and hence unable to adapt to the local Sub-MB changes. This paper proposes a Local Hybrid Pseudo-SSIM-SATD (LHPSS) Distortion Metric, operating at the Sub-MB level and satisfying the Triangle Equality Rule (≤). A detailed discussion of LHPSSs Psuedo-SSIM model will illustrate how SSIM can be perceptually scaled within the distortion metric space of SATD using non-logarithmic functions. Results of HD video encoded across different QPs will be presented showing the competitive bit usage under IbBbBbBbP prediction structure for similar image quality. Finally, the mode decision choices superimposed on the Intra frame will illustrate that LHPSS lowers the R-D curve as homogeneous regions are represented with larger block size.