Undirected, sparse and large-scaled networks existing ubiquitously in practical engineering are vitally important since they usually contain rich information various patterns. Matrix factorization (MF) technique is an efficient method to extract the useful latent factors (LFs) from LF model, which directly gives rise so-called MF model. However, most models cannot maintain some frequently encountered constraints such as nonnegativity of LFs symmetry target network. In addition, spite its...

Computation offloading from a mobile device to the edge server is an emerging paradigm reduce completion latency of intensive computations in mobile-edge computing (MEC). In order satisfy delay-sensitive tasks, time, including task uploading execution and results downloading time adopted as computational performance metrics for nodes that perform offloaded tasks devices. Therefore, how minimize by selecting optimal node MEC research importance. This work first investigates system consisting...

In wireless sensor networks, the node reliability can affect of data transmission. To analyze reliability, this paper defines both betweenness centrality and dependency degree for a to reflect its global local respectively. Based on above definition, reliability-based routing (GLRR) protocol is proposed guarantee transmission between source destination in network. GLRR, at first, some nodes, usually with greater among their neighbors limited range, will be selected as backtracking node....

Fuzzy <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$c$</tex-math></inline-formula> -means (FCM) clustering is a promising method to handle uncertainties in data clustering. However, the traditional FCM and most of its variants cannot address incomplete inputs. To this aim, novel fuzzy framework put forward perform highly accurate on data. It adopts twofold ideas: 1) Utilizing nonnegative latent factor...

Task allocation, which can be divided into offline task allocation and online is a significant issue in mobile crowdsensing (MCS). Unlike the scenario, since participants arrive at service dynamically, quantity of specific time space uncertain, hence it could affect quality efficiency completion. However, due to difficulty predicting real-time accurately, existing studies lack deep consideration participants. Therefore, this article investigates participant-quantity-aware problem. First,...

In mobile crowd sensing (MCS), complex tasks often require collaboration among multiple workers with diverse expertise and sensors. However, few studies consider the time redundancy of to complete a task collaboratively, subjective objective willingness participating in forming groups for different tasks. If solely focusing on enhancing workers' collaborate, it cannot guarantee minimum within group, resulting decrease group's efficiency. Similarly, if only aiming reduce may lead loss...

Mobile Crowd Sensing is an emerging sensing paradigm that employs massive number of workers' mobile devices to realize data collection. Unlike most task allocation mechanisms aim at optimizing the global system performance, stable matching considers workers are selfish and rational individuals, which has become a hotspot in MCS. However, existing lack deep consideration regarding effects competition phenomena complex behaviors. To address above issues, this paper investigates...

As a key research issue in mobile crowdsensing (MCS), recent studies on task recommendation have begun to focus recommending tasks participants according the learned participant preferences. The common drawbacks of these are that, one hand, factors affecting preferences predefined, which is not practical as influential quite complex and full map profiles needs be preexisted. On other they do consider how update dynamically. To overcome drawbacks, profile-free real-time method proposed this...

Nowadays, many applications of heterogeneous sensing wireless sensor networks (WSNs) employ more than one type nodes to acquire a variety data sources, which brings the dynamic diversity generated amount among different network regions. To adapt that and improve gathering efficiency, this paper first analyzes models according diversities generating rate operating mode then proposes scheme with mobile sink. In scheme, movement trajectory for sink is determined by using Hilbert space-filling...

Existing methods for tracking mobile sinks in Wireless Sensor Networks (WSNs) often incur considerable energy consumption and overhead. To address this issue, we propose a Detour-Aware Mobile Sink Tracking (DAMST) method via analysis of movement angle changes sinks, collecting data low-overhead efficient way. In the proposed method, while sink passes through region, it appoints specific node as region agent to collect information whole records nodes near or on its trajectory footprints. If...

Mobile crowd sensing (MCS) is a popular paradigm that recruits participants carrying devices to collect data for specific tasks in area. In an MCS system, when participant executes limited multiple location-based according different task accessing sequences, its executing time which depends on travelling path different. Therefore, how perform efficient planning find the optimal each of vital importance. this paper, we revisit problem and propose novel method based beetle swarm optimization...

The design of movement trajectories for mobile sink plays an important role in data gathering Wireless Sensor Networks (WSNs), as it affects the network coverage, and packet delivery ratio, well lifetime. In some scenarios, whole can be divided into subareas where nodes are randomly deployed. node densities these quite different, which may result a decreased ratio lifetime if trajectory cannot adapt to differences. To address problems, we propose adjustable method based on density WSNs. each...

Summary Feature selection is a useful method for fulfilling the data classification since inherent heterogeneity of and redundancy features are often encountered in current exploding era. Some commonly used feature algorithms, which include but not limited to Pearson, maximal information coefficient, ReliefF, well‐posed under assumption that instances distributed homogenously datasets. However, such an might be true practice. As such, presence imbalance, these traditional algorithms invalid...

With the explosive growth of crowdsourcing tasks, how to design appropriate task recommendation models that help workers find tasks and improve allocation efficiency has become a crucial issue in crowdsourcing. However, most existing methods based on Probabilistic Matrix Factorization (PMF) assume feature vectors are independent each other, therefore impairing accuracy recommendation. In this paper, potential dependency analysis model (PDA-TR) for is proposed. Firstly, worker-task rating...

Mobile crowd sensing (MCS) has attracted extensive attention as a promising method for environmental and data collection. However, due to the increasing computational tasks, bandwidth, computing pressure, traditional "Cloud-Edge–End" MCS is insufficient efficiently offload in real-time aggregation. Therefore, we consider novel framework based on "Cloud-Enhanced-Edge–End," uses idle users edge nodes (ENs) assist servers enhance power reduce delay energy consumption. To achieve efficient...

The working⁻sleeping cycle strategy used for sensor nodes with limited power supply in wireless networks can effectively save their energy, but also causes opportunistic node connections due to the intermittent communication mode, which affect reliability of data transmission. To address this problem, a collection scheme based on is proposed achieve efficient network mobile sink. In scheme, sink first broadcasts tag message start period, and all that receive will use probe forward own source...

Network connectivity, with its significant application value for data transmission and node cooperation, has drawn a great concern in recent years. Facing the heterogeneity complexity of IoT system, connectivity determination between nodes network is big challenge. In view this, this article proposes generic efficient method applications. This first characterizes parameters nodes, including direct connection probabilities degree centrality, betweenness centrality based on them, then...