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Great efforts have been driven to improve the optimal decision for network selection, which is significant for vertical handover to meet user's rapidly increased requirements. Unfortunately, the instability of the basic decisive parameters is usually ignored, resulting in a high misjudgement ratio. Therefore, this paper proposed a novel parameter estimation algorithm to bridge the observed values...
Data shuffling is one of the fundamental building blocks for distributed learning algorithms, that increases the statistical gain for each step of the learning process. In each iteration, different shuffled data points are assigned by a central node to a distributed set of workers to perform local computation, which leads to communication bottlenecks. The focus of this paper is on formalizing and...
Signal compression is essential for energy and bandwidth efficient communication and storage systems. In this paper, we provide two practical approaches for source compression of noisy sparse and non-strictly sparse (compressible) sources. The proposed schemes are based on channel coding theory to construct a source encoder that decreases the number of transmitted bits while preserving the fidelity...
Distributed machine learning is becoming increasingly popular for large scale data mining on large scale cluster. To mitigate the interference of straggler machines, recent distributed machine learning systems support flexible model consistency, which allows worker using a local stale model to compute model update without waiting for the newest model, while limiting the asynchronous step in a certain...
Due to limited resource, noise and unreliable link, data loss and sensor faults are common in medical body sensor networks (BSN). Most available works used data reconstruction to improve data quality in traditional wireless sensor networks (WSN). However, existing data reconstruction schemes using redundant information of WSN can not provide a satisfactory accuracy for BSN. In light of this, a Bayesian...
Data-driven solutions to Electric Vehicle (EV) range estimation is attracting attention recently due to the prevalence of Internet of Things (IoT). However, there raise the Big Data problems with the increased volume and number of sensory sources of unstructured data collected from the EV equipped with In-Vehicle Networks. This means that traditional statistical analysis and Machine Learning tools...
White Space (WS) Networking crucially relies on the active monitoring of spatio-temporal spectrum usage (to identify WS opportunities). To achieve this, one way is to gather spectrum data via wide-area sensor deployment and construct better Radio Environment Maps (REMs) with spatial models such as Kriging and Gaussian Process (GP). An economically viable alternative is via incentivized crowdsourcing,...
Nowadays people are carrying their mobile devices wherever they go, and as social beings they interact with others all day long. Thus, by exploiting this massive use of smart devices they provide a way to be co-located using only their captured environmental radio signals. In this paper, we design a co-location system that finds groups of people, in real-time, with high accuracy, by exploiting the...
Mobile crowdsensing emerges as a promising sensing paradigm through leveraging the diverse embedded sensors in massive mobile devices. A key objective in mobile crowdsensing is to efficiently schedule mobile device users to perform multiple sensing tasks. Prior work mainly focused on the interactions between the task layer and the user layer, without considering the similarity of tasks' data requirements...
The performance of Smart Data Pricing (SDP) highly depends on the accuracy and reliability of measuring network bandwidth usage. The existing Internet protocol uses the distributed control, and the transport network protocols run together inside the routers and switches. However, it is hard to manage and retrieve online and precise measurements from the networks due to the large number of traffic...
The increasing number of connected vehicles in densely populated urban areas provides an interesting opportunity to counteract the high wireless data demands in high density and highly mobile scenarios. The idea is to support the macro base station (BS) with a secondary communication tier composed of a set of smart and connected vehicles that are in movement in the urban area. As a first step towards...
In virtualized networks, network functions are delivered as software running on generic hardware allowing service providers to dynamically allocate resources based on traffic and service demands. Network Function Virtualization (NFV) is becoming a key enabler and consequently a hot research topic. Dynamic scaling of resources in NFV is a highly important challenge towards its implementation in real-life...
The Energy Harvesting-aware Distributed Queuing access protocol (EH-DQ) is presented in this paper as a novel Medium Access Control protocol for wireless Machine-to-Machine networks with energy harvesting capabilities. EH-DQ is theoretically modeled to analyze its performance. A performance comparison with a Time Division Multiple Access (TDMA) and an EH-aware Reservation Dynamic Frame Slotted-ALOHA...
The first standardized version of G.fast has been conceived to provide gigabit internet access from the distribution point (DP). Low transmit levels along its operational frequency range and low maximum aggregate transmit power (MAXATP) have been specified to restrict its electromagnetic emissions and enable the use of power available at customer premises to feed its access systems. Power constraints...
Content Delivery Networks (CDN) and their globally dispersed caches host a myriad of User Generated Videos (UGV) to meet end-user requests with quality of service. To efficiently utilize the limited storage of the caches, it is imperative to improve the hit ratio of UGVs. In contrast to the traditional static content, UGV popularity is highly dynamic and dependent on end-user behavior. Therefore,...
In this work, we study the joint optimization of edge caching and data sponsoring for a video content provider (CP), aiming at reducing the content delivery cost and increasing the CP's revenue. Specifically, we formulate the joint optimization problem as a two-stage decision problem for the CP. In Stage I, the CP determines the edge caching policy (for a relatively long time period). In Stage II,...
Data randomization or scrambling has been effectively used in various applications to improve the data security. In this paper, we use the idea of data randomization to proactively randomize the spectrum (re)allocation to improve connections' security. As it is well-known that random (re)allocation fragments the spectrum and thus increases blocking in elastic optical networks, we analyze the tradeoff...
Unmanned aerial vehicles (UAVs) are expected to be used extensively in the near future in applications such as aerial surveillance, transportation, and disaster assistance. The conditions under which UAVs operate are different from those of conventional piloted aircrafts. This necessitates development of new air-to-ground (AG) propagation channel models for UAVs. To our best knowledge, there are limited...
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