Crowdsourcing through web technologies has emerged as a key method and tool for conducting distributed work. There are new platforms constantly emerging that aim to provide crowdsourcing opportunities on mobile phones. However, most of these systems are very specific to certain types of tasks and do not address various mobile resource constraints experienced in developing countries such as India.

We propose and design a new platform Wallah that tries to address these limitations with a broad vision to make crowdsourcing opportunities pervasively available and feasible to do (i.e., at all times, locations, and with minimum investment in infrastructure from the crowd-workers). It supports task-centric applications to minimize the impact of screen size and facilitates caching of crowdsourcing tasks to deal with network limitations. Wallah supports both physical as well as virtual crowdsourcing tasks. The current version of Wallah implements an end-to-end platform for Android devices and includes five different task-centric applications for different categories of crowdsourcing tasks (human OCR, image tagging, language translation, audio transcription, and video tagging) developed by us. We evaluated the system with a 2 week pilot deployment among 59 crowd-workers where over 16000 tasks were performed. We analyzed the platform usage in detail and present descriptive statistics related to task completion time and task accuracy rates with other analysis such as the impact of screen size on task completion time and accuracy. We also conducted a post study survey to get participant's qualitative feedback and their perceived difficulties of different crowdsourcing tasks.

In this contribution, the performance of an uplink CDMA system is analyzed in the context of frequency selective fading channels. Using game theoretic tools, a useful framework is provided in order to determine the optimal power allocation when users know only their own channel (while perfect channel state information is assumed at the base station). We consider the realistic case of frequency selective channels. This scenario illustrates the case of decentralized schemes and aims at reducing the downlink signaling overhead. Various receivers are considered, namely the Matched filter, the MMSE filter and the optimum filter. The goal of this paper is to derive simple expressions for the non-cooperative Nash equilibrium as the number of mobiles becomes large. To that end we combine two asymptotic methodologies. The first is asymptotic random matrix theory which allows us to obtain explicit expressions for the impact of all other mobiles on any given tagged mobile. The second is the theory of non-atomic games along with the Wardrop equilibrium concept which allows us to compute good approximations of the Nash equilibrium as the number of mobiles grow.

There are a number of challenges facing the High Performance Computing (HPC) community, including increasing levels of concurrency (threads, cores, nodes), deeper and more complex memory hierarchies (register, cache, disk, network), mixed hardware sets (CPUs and GPUs) and increasing scale (tens or hundreds of thousands of processing elements). Assessing the performance of complex scientific applications on specialised high-performance computing architectures is difficult. In many cases, traditional computer benchmarking is insufficient as it typically requires access to physical machines of equivalent (or similar) specification and rarely relates to the potential capability of an application. A technique known as application performance modelling addresses many of these additional requirements. Modelling allows future architectures and/or applications to be explored in a mathematical or simulated setting, thus enabling hypothetical questions relating to the configuration of a potential future architecture to be assessed in terms of its impact on key scientific codes.

This paper describes the Warwick Performance Prediction (WARPP) simulator, which is used to construct application performance models for complex industry-strength parallel scientific codes executing on thousands of processing cores. The capability and accuracy of the simulator is demonstrated through its application to a scientific benchmark developed by the United Kingdom Atomic Weapons Establishment (AWE). The results of the simulations are validated for two different HPC architectures, each case demonstrating a greater than 90% accuracy for run-time prediction. Simulation results, collected from runs on a standard PC, are provided for up to 65,000 processor cores. It is also shown how the addition of operating system jitter to the simulator can improve the quality of the application performance model results.

Hospitals and residential homes have a significant need for monitoring and recognising wandering-o (e.g. elopement) older people with cognitive impairments because of the serious consequences arising from wandering-o such as disappearances and serious injuries, for example, from collisions with vehicles in parking lots. Due to increasing ageing populations across the globe we can expect wandering-o to become a signicant problem of scale aecting all of us. Existing technologies used to address wandering-o are inadequate for providing close supervision as they use proximity based sensing that often lead to false alarms. In this study, for the rst time, we try to mitigate false alarms by identifying the traversal direction and traversal path used by people instrumented with a single low cost batteryless UHF RFID tag. Our approach uses a particle ltering (PF) based technique with Received Signal Strength Indicator (RSSI) maps obtained from scene analysis to continuously track a person wearing an RFID tag over their attire. Using real-time spatial and temporal data obtained from the PF based tracking algorithm, we develop two algorithms: i) tag traversing di rection (TD) algorithm to identify the tag bearer's moving direction (e.g. moving out of a room); and ii) tag traversing path detection algorithm (TPD) to estimate the traversal path used by the tag bearer. Our extensive experiments with 14 young adult volunteers show that: i) our TD algorithm can identify the moving direction of a person with 100% ac- curacy; ii) our TPD algorithm reduces the false alarms to < 9%, when detecting the traversing path used while eloping; and iii) our algorithms can be implemented in a dierent environment without further scene analysis.

A recent study revealed that every fourth German adult drinks less than 1.5 litres a day. In the long term, this leads to dehydration and can cause confusedness, faint, or can even be mortal. To overcome their problem, people affected use reminder signals which they often miss or yet deactivate because they are too obtrusive. In this paper we present WaterJewel, an LED-illuminated bracelet which reminds the user to drink, as well as it rises the user's awareness for their drinking frequency in an unobtrusive way. Eight single light spots on the bracelet indicate the amount of drinks taken. Another light spot presents the time elapsed since the last drink. We found that with WaterJewel, people manage to drink 2 litres a day and drink more regularly than with current approaches.

WAVE is an API for Android OS which which allows for easy management of body sensor networks (BSNs) on mobile platforms. It presents a simple framework for health-oriented applications by providing functionality for data collection from sensors and data processing. CalFit is an interactive application built using WAVE that leverages the power of social influence to promote physical activity.

This paper proposes a simple procedure to ensure burst transmission without losses in Optical Burst Switching ring networks. The contention problem is solved by providing a scheme that pre-assigns, to each communication, a given wavelength and an offset window. This approach does not need any additional control information and, since burst contention is avoided, the network capacity and the wavelength utilization are maximized under dynamic traffic assumptions. The study is done by using techniques from graph theory. In particular, the so-called (acyclic) restriction digraphs provide a sharp lower bound for the number of required wavelengths, and support a greedy algorithm for assigning a suitable offset window to each communication. An alternative formulation of the obtained schemes, in terms of matrices, is also discussed. Simulation results of different feasible solutions are provided, showing low transmission delays and quite balanced wavelength utilization.

Efficient routing and wavelength assignment (RWA) in wavelength-routed all-optical networks is critical for achieving high efficiency over the backbone links. Extensive research has been conducted to find strategies to solve the RWA problem with exact network state available at the time of path selection. We consider the problem of minimizing the blocking probability in an all-optical network with partial wavelength conversion and with imprecise network state information. We model imprecision in link-state information (wavelength availability) probabilistically and use Markovian analysis to predict the availability of each link based on its previous advertisement and the estimated average traffic over the link. The estimated probabilities are then used to find the most probable path between a source destination pair. We also consider the problem of lightpath establishment with 1+1 protection. We use the same Markovian model to predict the link availability and then use the probabilistic estimate and a modified version of flow algorithm to find two link-disjoint paths between the source and destination. Simulations are conducted to compare the performance of random-fit and the proposed wavelength assignment schemes. We have also performed extensive simulations to study the performance of the proposed flow algorithm. It is observed that the proposed wavelength assignment scheme performs significantly better in terms of blocking probability than conventional wavelength assignment schemes.

With the huge capacity, wavelength division multiplexing (WDM) optical networks are predominantly used as the transport infrastructure to carry inter-domain traffic for client networks. WDM optical networks offer wavelength granularity high-capacity optical connections, whereas client traffic flows are usually at sub-wavelength granularity. Traffic grooming in WDM optical networks refers to the aggregation of low-rate client traffic flows onto high-capacity optical connections. When client traffic randomly arrives/departs, it is called dynamic traffic grooming. This paper focuses on wavelength converter placement for dynamic traffic grooming in optical networks. We propose an adaptive traffic load based converter placement heuristic and also study several other heuristics. The numerical results indicate that the adaptive traffic load based heuristic can obtain a similar performance as the greedy heuristics, in both blocking probabilities and throughputs, with lower computation complexity.

In this paper, a Wavelength Tunable Optical Burst Ring Network (WTOBRN) test-bed is introduced. In this WTOBRN test-bed, ring topology is adapted to play the role as Metropolitan Area Network (MAN). Six optical wavelengths mixed in one fiber by Wavelength Division Multiplexing (WDM) technology are arranged along the ring. Some new technology such as advanced token protocol and wavelength tunable receivers are employed to avoid packet collision. Advanced token protocol named M-Token can ensure free-packet-collision along the ring. At destination node, Acoustical Optical Tunable Filter (AOTF) using as tunable receivers can decrease packet collision. Performance of the test-bed is verified by experimental results.