Several studies were interested in social shared content as rewarding source to enrich user's profile. In this context, we highlight the importance of considering the user's relationship strength to derive rel...
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Several studies were interested in social shared content as rewarding source to enrich user's profile. In this context, we highlight the importance of considering the user's relationship strength to derive relevant social profile. We focus on egocentric network community-based user profiling process (CoBSP) which considers only binary connections between people. In real life, social connections are not merely binary but have associated weights that record people's relation strength. We aim to enhance the effectiveness of CoBSP process by integrating ties strength in the user's profiling process. Our motivation stems from the intuition that people having the strongest relationships withthe profiled user may reveal more valuable information about him. the first experiments conducted on scientific publications networks (DBLP/ResearchGate) are promising and show the relevance of our prior premise. However, we should conduct further experiments to completely validate the effectiveness of our proposition.
this research proposal investigates the promise of Opportunistic or Delay-tolerant networks (DTNs) for efficient and effective information dissemination in the context of natural disasters. Natural disasters affect th...
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ISBN:
(纸本)9781450344166
this research proposal investigates the promise of Opportunistic or Delay-tolerant networks (DTNs) for efficient and effective information dissemination in the context of natural disasters. Natural disasters affect the traditional communication infrastructure and thereby call for different unconventional techniques to meet communication requirements. this is because traditional communication infrastructure may get incapacitated due to the severity of the disaster or lack of power supply. Fortunately, majority of population these days owns various wireless devices, such as smart phones and tablets, with multiple communication interfaces (Wi-Fi and Bluetooth). these devices withtheir alternative communication capabilities can be harnessed in a disaster aftermath in the form of DTNs. the rescue and relief operation immediately after disaster is challenging mainly due to the lack of suitable map based navigation assistance and inadequate information regarding resource inventory. Offering map based navigation services and adequate information regarding resource inventory over DTNs become challenging mainly due to unstable connectivity, modified road networks and decentralized resource management at warehouses. these limitations inspire us to explore the possibilities of offering navigation and distributed resource management services over DTNs.
Vehicular ad-hoc networks (VANETs) play a vital role in enabling Intelligent Transport Services (ITS). the well known Dedicated short range communication (DSRC) requires dedicated hardware installation, which slows do...
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ISBN:
(纸本)9781450344166
Vehicular ad-hoc networks (VANETs) play a vital role in enabling Intelligent Transport Services (ITS). the well known Dedicated short range communication (DSRC) requires dedicated hardware installation, which slows down the penetration of ITS. this study analyzes the capability of using Wi-Fi Direct (WD) as an alternative technology for ITS applications. To this end, A simulation study is carried out to compare the performance of WD with DSRC. Network simulator NS3 is used along withthe traffic simulator named SUMO for the study. Initial results that indicate the potential of WD are presented with future extensions and goals.
Incremental Least means squares algorithm is one of the simplest algorithm for parameter estimation in distributed wireless networks, which find a wide range of applications from monitoring environmental parameters to...
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Incremental Least means squares algorithm is one of the simplest algorithm for parameter estimation in distributed wireless networks, which find a wide range of applications from monitoring environmental parameters to satellite positioning. Digital implementation of adaptive filters results in quantization errors and finite precision errors, which makes the ILMS algorithm to suffer from drift problem. Incremental Leaky LMS algorithm introduces a leakage factor in the update equation and overcomes the drift problem. But the overall performance of ILLMS is similar to ILMS in terms of convergence speed. To overcome this an incremental Modified Leaky LMS is proposed based on MLLMS algorithm which in turn derived from the Least Sum of Exponentials algorithm. LSE algorithm employs sum of exponentials of errors in its cost function and it results in convex and smooth error surface with more steepness, which results in faster convergence rate. Simulation results prove that the proposed IMLLMS outperforms the ILLMS.
Mobile offloading overcomes the resource limitations of offloader devices by splitting resource-intensive tasks and allocating subtasks to nearby offloadee devices. In processing its subtask, each offloadee effectivel...
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ISBN:
(纸本)9781509066001
Mobile offloading overcomes the resource limitations of offloader devices by splitting resource-intensive tasks and allocating subtasks to nearby offloadee devices. In processing its subtask, each offloadee effectively executes foreign and untrusted code which might both harm the device and exhaust its resources. Given the personal nature and constrained resources of offloadee devices, such as smartphones, precise control at the offloadee over the execution environment of offloaded tasks as well as the provided and consumed resources then is a natural requirement for the success of offloading approaches. We thus contribute a mechanism for fine-grained resource control of local task execution, benefitting allocation approaches by precisely assessing, advertising, and guaranteeing offloadee processing resources. Our design protects local device integrity and usability by isolating the execution of each task in a dedicated Linux container with precisely defined resource constraints. We highlight the performance and immediate applicability of our design through a prototypical implementation using LXC containers on COTS Android smartphones that achieves controllable task execution at minimal costs: Each container starts up in only 2 ms, imposes less than 5 % computation overhead, and consumes only 10MB of memory.
Real-time applications play a significant role in the area of VANET, and are mainly required for these kinds of networks. On the other hand, when the number of messages received by vehicles increases in the network, t...
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Real-time applications play a significant role in the area of VANET, and are mainly required for these kinds of networks. On the other hand, when the number of messages received by vehicles increases in the network, then the applied computation load becomes extremely high and consequently, delay on the message authentication process significantly increases. this paper is presented withthe aim of introducing a novel cooperative message authentication (CMA) scheme for VANET, the main purpose of which is alleviating the computation load on vehicles while verifying messages by using two-part identity-based signature. the scheme enables vehicles to verify only a limited number of the total received massages, and uses other vehicles' authentication results for the rest of the messages. the security arrangements to prevent the free riding attacks have also been considered. Our CMA method uses batch verification and does not use pairing operation and public key certificates. therefore, our proposed CMA scheme achieves considerably low computation load compared to the related works. Performance evaluation and comparison results of the computational complexity show the efficiency, practicality and deployability of our proposal.
the pervasiveness of mobile phones and the increasing sensing capabilities of their built-in sensors have made mobile crowd sensing (MCS) a promising approach for large-scale event detection and collective knowledge f...
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ISBN:
(纸本)9781509066001
the pervasiveness of mobile phones and the increasing sensing capabilities of their built-in sensors have made mobile crowd sensing (MCS) a promising approach for large-scale event detection and collective knowledge formation. In a typical MCS system, the crowdsourcer purchases sensing data from some mobile phone users (i.e., contributors) and sells it to consumers for revenue. this kind of sensing data exchange has its unique challenges in practical MCS systems. On one hand, the crowdsourcer wants to maximize the information utility to get the most revenue under heterogeneous requests from the consumers while offering incentives to strategic contributors. On the other hand, the contributors need to make optimal real-time sensing and data selling decisions by considering their real-time sensing cost and quality of information, in order to maximize their own profit. In this paper, we propose a novel Information-driven Data Auction (IDA) scheme for data exchange in practical stochastic MCS systems, which offers optimal strategies for boththe crowdsourcer and the contributors. By applying stochastic Lyapunov optimization and mechanism design theory, IDA is able to achieve a near-optimal time-averaged system-wide utility, while offering incentives to the contributors. Moreover, IDA achieves favourable economic properties including truthfulness, individual rationality, and budget balance. We demonstrate the efficacy of IDA through rigorous theoretical analysis and comprehensive simulations.
UAVs can support different applications, such as forest fire surveillance and precise agriculture. UAVs' service-on-demand preference drives the need for multiple UAVs to enhance surveillance coverage and data sta...
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ISBN:
(纸本)9781509066001
UAVs can support different applications, such as forest fire surveillance and precise agriculture. UAVs' service-on-demand preference drives the need for multiple UAVs to enhance surveillance coverage and data stability. Due to the limited capacity of the UAV, UAVs desire network coordination based on the importances of collected data. For example, UAVs at different locations may have different priorities of data forwarding tasks while the required data sizes of different tasks are varying. In this paper, we propose a system framework for UAV array to structure and prioritize the data forwarding based on i) forward-looking channel quality; ii) priorities of tasks of multimodal data on demand. Our proposed distributed real-time framework aims to optimize effective data throughput given a channel quality and effective scheduling of the channel usage among multiple UAVs. We conducted extensive evaluations using multiple UAVs and results show that our modeling of forward-looking channel quality prediction achieves 90% accuracy. Moreover, our scheduling algorithms can effectively optimize the overall data quality of forwarding tasks between UAVs and the base station.
Nowadays, 3D reconstruction has been introduced in monitoring the package placement in logistic industry-related applications. Existing 3D econstruction methods are mainly based on computer vision or sensor-based appr...
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ISBN:
(纸本)9781509066001
Nowadays, 3D reconstruction has been introduced in monitoring the package placement in logistic industry-related applications. Existing 3D econstruction methods are mainly based on computer vision or sensor-based approaches, which are limited by the line-of-sight or battery life constraint. In this paper, we propose RF-3DScan to perform 3D reconstruction on tagged packages via passive RFID, by attaching multiple reference tags onto the surface of the packages. the basic idea is that by moving the antenna along straight lines within a constrained 2-dimensional space, the antenna obtains the RF-signals of the reference tags attached on the packages. By extracting the phase differences to build the angle profile for each tag, RF-3DScan can compare the angle profiles of the different reference tags and derive their relative positions, then further determine the package orientation and stacking for 3D reconstruction. We implement RF- 3DScan and evaluate its performance in real settings. the experiment results show that the average identification accuracy of the bottom face is about 92.5%, and the average estimation error of the rotation angle is about 4.08 o .
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