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Link prediction is a fundamental research issue in complex network, which can reveal the potential relationships between users. Most of link prediction algorithms are heuristic and based on topology structure. Weisfeiler–Lehman Neural Machine (WLNM), regarded as a new-generation method, has shown promising performance and thus got attention in link prediction. WLNM extracts an enclosing subgraph of each target link and encodes the subgraph as an adjacency matrix. But it does not consider the relationship between other links of the enclosing subgraph and target links. Therefore, WLNM does not make full use of the topology information around the link, and the extracted enclosing subgraph can only partially represent the topological features around the target link. In this work, a novel approach is proposed, named weighted enclosing subgraph-based link prediction (WESLP). It incorporates the link weights in the enclosing subgraph to reflect their relationship with the target link, and the Katz index between nodes is used to measure the relationship between two links. The prediction models are trained by different classifiers based on these weighted enclosing subgraphs. Experiments show that our proposed method consistently performs well on different real-world datasets. [ABSTRACT FROM AUTHOR]

Topology control has drawn considerable attention in underwater wireless sensor networks. With the complexity of the underwater environment considered, the topological model of a three-dimensional dense network is adopted. The partition unit, cluster, and temporary control node are first defined. A clustering dormancy scheduling algorithm is then proposed. Accordingly, a vulnerability repair algorithm is presented with consideration of the vulnerability of sensor nodes to death due to external factors. The failure node, coverage vulnerability, coverage matrix, key position, and supplementary node are defined in the proposed algorithm. The algorithm also uses the coverage matrix and the vulnerability edge nodes to determine whether the overlay vulnerability requires repair. Experimental results indicate that this algorithm is more effective and efficient compared with similar algorithms. [ABSTRACT FROM AUTHOR]

All major insecticidal genes of Bacillus thuringiensis var. israelensis (Bti) are controlled by the sporulation-specific sigma factor Sigma E (sigE), while sigE is negatively regulated by Sigma K (sigK). Therefore, knocking out sigK plays an important role in regulating the expression of insecticidal genes in Bti. A sigK deletion mutant of B. thuringiensis var. israelensis strain Bt-59, Bt59(ΔsigK), was constructed by homologous recombination and characterized. The sigK deletion resulted in no mature spores and delayed mother cell lysis from T25 to T60, while the genetically complemented strain, Bt59(HFsigK), had mother cell lysis at T25. Compared to Bt-59, sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) analysis indicated that the expression of Cry4Aa2/4Ba1 and Cyt1Aa1 proteins in Bt59(ΔsigK) increased approximately 1.67 and 1.21 times, respectively. However, there was no significant change in Cry11Aa1 protein expression between the two strains. Bioassay results showed that the sigK deletion mutation slightly reduced the insecticidal activity of Bt-59 against Culex pipiens pallens and did not obviously affect activity against Aedes albopictus. [ABSTRACT FROM AUTHOR]

Mobile edge computing (MEC) utilizes wireless access network to provide powerful computing resources for mobile users to improve the user experience, which mainly includes two aspects: time and energy consumption. Time refers to the latency consumed to process user tasks, while energy consumption refers to the total energy consumed in processing tasks. In this paper, the time and energy consumption in user experience are weighted as a mixed overhead and then optimized jointly. We formulate a mixed overhead of time and energy (MOTE) minimization problem, which is a nonlinear programming problem. In order to solve this problem, the block coordinate descent method to deal with each variable step by step is adopted. We further analyze the minimum value of delay parameters in the model, and examine two special cases: 1-offloading and 0-offloading. In 1-offloading, all the task data is offloaded to MEC server, and no data offloaded in 0-offloading. The necessary and sufficient conditions for the existence of two special cases are also deduced. Besides, the multi-user situation is also discussed. In the performance evaluation, we compare MOTE with other offloading schemes, such as exhaustive strategy and Monte Carlo simulation method-based strategy to evaluate the optimality. The simulation results show that MOTE always achieves the minimal overhead compared to other algorithms. [ABSTRACT FROM AUTHOR]

Objective: To explore whether the distance of rectal neuroendocrine neoplasms from the anal margin has an impact on the prognosis of patients and evaluate lymphatic metastases risk score for colorectal neuroendocrine neoplasms (NENs). Methods: Clinical pathological and follow-up data of 71 patients identified as colorectal neuroendocrine neoplasms by pathology from July 2011 to July 2019 were carefully collected. Results: Among 71 patients with colorectal NENs, most of the tumors were rectal NENs (62 cases). A total of 26 patients were in the presence of lymph node metastasis, and 44 patients had negative lymph nodes. Patients with lesions from the anal margin > 5 cm in rectum have a better prognosis (P = 0.022). Tumor stage (P = 0.034) and grade (P = 0.001) were independent risk predictors of lymphatic metastases. We developed a lymphatic metastasis risk score for rectal NENs, and patients with the score ≥ 7.5 were more likely to develop lymph node metastases (area 0.958, 95% CI 0.903–1.000, P = 0.000) with a sensitivity of 72.2% and a specificity of 97.3%. Conclusion: Patients with lesions from the anal margin > 5 cm and lymphatic metastasis risk score ≥ 7.5 should be treated actively. [ABSTRACT FROM AUTHOR]

Contents typed via keyboards prove to be vulnerable to attacks based on acoustic emanations analysis. However, previous works achieve the attacks under controlled environment, e.g., neglecting the noises or requiring the keyboard to be located in fixed locations. In this study, we present a localization-free online keystroke tracking system (LOL), which enables people to use prior knowledge obtained from the keyboard in one location to recognize real-time keystrokes of the same type of keyboard in any other places, despite various background noises. Combined with support vector machine, we design an detection model to separate keystroke signals from noises. By analyzing the properties of acoustics transmission, we propose an angle-based sampling method with a single microphone to decrease the dependence on certain locations, and it also increases the diversity of signals in the meantime. Our real-world experiments demonstrate a 99.47% keystroke detection rate, a 97.27% recognition accuracy under ideal condition, and an 84.55% content recovery accuracy despite changing locations of the keyboard. Most commercial off-the-shelf sound recording devices, e.g., smartphones, can be used in our system to record acoustic emanations from keystrokes. LOL could attract more community to study security of keyboard devices and promote users to enhance privacy protection awareness. [ABSTRACT FROM AUTHOR]

IoT (Internet of Things) security has become a severe yet not well solved problem attracting increasing research attention as well as industrial concerns. Location-based access control approaches, such as Wi-Fi geo-fencing, promise to fulfill the needs of preventing unauthorized access to IoT systems. We propose a crowdsourcing method for location aware security access control, namely LaSa, which is able to confine wireless network access inside certain physical areas only using a single commercial Access Point (AP). Specifically, LaSa detects whether a user enters or exits a room by discovering and recognizing the unique signal patterns. It combines the Received Signal Strength (RSS), Channel State Information (CSI), and coarse Angle of Arrival (AoA) data to improve the accuracy of user classification for accessing the wireless network. Real-world experimental results show that LaSa can achieve a 97.0% accuracy of identification of unauthorized users while maintaining a low false blocking rate of authorized users as low as 3.3%. LaSa is designed to be straightforward for integration with commercial APs and deployment to home and business Wi-Fi environments. [ABSTRACT FROM AUTHOR]

In an industrial production process, the leakage of continuous objects poses a serious threat to production safety. In this paper, a diffusion distance-based predictive tracking algorithm is proposed for industrial wireless sensor networks (IWSNs), aiming to timely track the boundary of a continuous object after the occurrence of a leak. Based on the assumption that the motion of the continuous object follows an appropriate diffusion model, sensor nodes are able to capture environmental parameters for establishing the mathematical expression of the model locally. Through building up the relation of diffusion radius with time, each node predicts diffusion scope of the continuous object at different times and makes a judgment about whether it is suitable to be a boundary node. Moreover, to achieve high energy-efficiency, a sleep/wake cycle is introduced to involve a small number of nodes in the process of tracking, while the rest of nodes stay idle until an object approaches. Finally, a cluster-based competitive mechanism is proposed for reporting the location of boundary nodes. Simulation results demonstrated that our proposal is able to track the diffusion of continuous objects with high energy-efficiency. [ABSTRACT FROM AUTHOR]

Socialized recommender system recommends reliable healthcare services for users. Ratings are predicted on the healthcare services by merging recommendations given by users who has social relations with the active users. However, existing works did not consider the influence of distrust between users. They recommend items only based on the trust relations between users. We therefore propose a novel deep learning-based socialized healthcare service recommender model, which recommends healthcare services with recommendations given by recommenders with both trust relations and distrust relations with the active users. The influences of recommenders, considering both the node information and the structure information, are merged via the deep learning model. Experimental results show that the proposed model outperforms the existing works on prediction accuracy and prediction coverage simultaneously, even for cold start users or users with very sparse trust relations. It is also computational less expensive. [ABSTRACT FROM AUTHOR]

Single-instruction-set architecture (Single-ISA) heterogeneous multi-core processors (HMP) are superior to Symmetric Multi-core processors in performance per watt. They are popular in many aspects of the Internet of Things, including mobile multimedia cloud computing platforms. One Single-ISA HMP integrates both fast out-of-order cores and slow simpler cores, while all cores are sharing the same ISA. The quality of service (QoS) is most important for virtual machine (VM) resource management in multimedia mobile computing, particularly in Single-ISA heterogeneous multi-core cloud computing platforms. Therefore, in this paper, we propose a dynamic cloud resource management (DCRM) policy to improve the QoS in multimedia mobile computing. DCRM dynamically and optimally partitions shared resources according to service or application requirements. Moreover, DCRM combines resource-aware VM allocation to maximize the effectiveness of the heterogeneous multi-core cloud platform. The basic idea for this performance improvement is to balance the shared resource allocations with these resources requirements. The experimental results show that DCRM behaves better in both response time and QoS, thus proving that DCRM is good at shared resource management in mobile media cloud computing. [ABSTRACT FROM AUTHOR]

In Device-to-Device (D2D) communications of massive Multiple-Input Multiple-Output (MIMO) system, the inter-channel interference (ICI) can severely deteriorate the entire system performance. The beamforming technique can be used to alleviate this situation. Thus the localization of the users' equipment (UE) should be known as a prior. In wireless communication, due to the effect of multipath, the model of incident signal should be regarded as distributed sources instead of point sources. In this paper, we propose a 2-D DOA estimation algorithm for coherently distributed (CD) sources based on conformal array. First, three rational invariance relationships are constructed based on generalized steering vectors (GSVs). Then the propagator method (PM) is used for estimating three rational invariance matrices. Finally, the 2-D DOA of CD sources can be obtained from the eigenvalues of three rational invariance matrices. Without spectrum peaking searching, and estimation and eigendecomposition of sampling covariance matrix, the proposed algorithm has low computational complexity. For the condition with a large amount of data, the distributed and parallel PM is proposed to deal with this problem. Simulation results verify the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

With the widespread use of wireless sensor networks, more and more applications require energy efficient and low packet loss rate data collection methods. Recently, the concept of 'mobile' is introduced in various mechanisms to meet the needs of this kind. In this paper, a honeycomb structure based data gathering scheme, HSDG, is proposed for wireless sensor networks with a mobile sink. By partitioning the network into a honeycomb structure and giving each partition a direction value, every sensor node can obtain the latest location of the mobile sink dynamically with a small amount of broadcasting overhead. HSDG uncouples the moving strategy of mobile sink from the data forwarding mechanism, and three subscheme HSDG_RM, HSDG_DGM, and HSDG_EGM are proposed. Our schemes are investigated from average energy consumption, maintenance cost, packet loss rate and the number of packets collected. Compared with BTDG and ALURP, HSDG_DGM is the most energy efficient with a low packet loss rate. [ABSTRACT FROM AUTHOR]

In order to improve the frequency spectrum availability and evade insecurity frequency range, the cognitive radio is introduced in wireless sensor network (WSN), which constructs the cognitive wireless network (CWN). The dynamic spectrum access (DSA) is used in CWN as the spectrum access scheme. In this paper, sensor nodes of mobile wireless sensor network (MWSN) are deployed based on the prior information of the deployment environment. The idea of CWN is introduced in MWSN. A distributed direction-of-arrival (DOA) estimation algorithm is proposed. The clustering of nodes constructs a sub-NWSN which acts as the sensor array used for DOA estimation. The Fourier domain (FD) root multiple signal classification (root-MUSIC) algorithm is applied for DOA estimation of sub-MWSN with arbitrary topology structure. The weight values of sub-MWSNs can be formulated as a function of the number of nodes, snapshot number and battery capacity of nodes. The total cost spectrum function is achieved finally. The improved performance of distributed FD root-MUSIC algorithm is verified by comparing with the manifold separation technique. [ABSTRACT FROM AUTHOR]

In a resource-constrained wireless sensor network, energy efficiency is a principle issue for monitoring the movement of continuous objects, such as wild fire and hazardous chemical material. In this paper, a continuous object tracking scheme with two-layer grid model (TGM-COT) is proposed. To address the problem of boundary distortion caused by uneven node distribution, we put forward a novel mechanism for boundary nodes identification. Furthermore, a streamlining mechanism is designed to reduce the amount of uploaded data. Simulation results demonstrate that, without sacrificing additional energy consumption, TGM-COT is able to achieve high tracking accuracy and significantly reduce the communication overhead. [ABSTRACT FROM AUTHOR]

In Ad hoc network, nodes have the characteristics of limited energy, self-organizing and multi-hop. For the purpose of improving the survivability of Ad hoc network effectively, this paper proposes a new algorithm named EMDWCA (Based on Energy, Mobility and Degrees of the nodes on-demand Weighted Clustering Algorithm). The LEACH algorithm is used to cluster the Ad hoc network in the first election, but the EMDWCA is used in the second election. By considering the appearances, disappearances, and communication link failures of the mobile nodes, this algorithm constructs the topology of Ad hoc network based on a small-world network model. To make sure that nodes can still communicate in the following election cycles, it improves the stability of the network topology and overall network invulnerability. The network is analyzed and simulation experiments are performed in order to compare the performance of this new clustering algorithm with the weighted clustering algorithm (WCA) in terms of the correctness, effectiveness, and invulnerability of the networks. The final result proves that the proposed algorithm provides better performance than the original WCA algorithm. [ABSTRACT FROM AUTHOR]

In wireless multimedia sensor networks (WMSNs), the energy consumption of multimedia data type are much higher than that of traditional wireless sensor networks (WSNs). Heavy multimedia data relaying operation causes not only single sensor node dead early, but also 'hot spots' problem. In this paper, a novel energy efficient data gathering scheme with a mobile sink for WMSNs, BTDGS, is proposed. It is based on a virtual binary-tree infrastructure. The mobile sink moves along a predefined circle trajectory, and sensor nodes relay data packages in a greedy manner. The process of BTDGS data gathering includes sink location broadcasting phase, data collection phase, and sink leaving broadcasting phase. The simulation results show that our BTDGS is an energy effective, reliable, timely, and sojourn time adaptive data gathering scheme. It is feasible and suitable for WMSNs. [ABSTRACT FROM AUTHOR]

The multiple input and multiple output (MIMO) and smart antenna (SA) technique have been widely accepted as promising schemes to improve the spectrum efficiency and coverage of mobile communication systems. The definition of direction-of-arrival (DOA) estimation is that multiple directions of incident signals can be estimated simultaneously by some algorithms using the received data. The conventional DOA estimation of user equipments (UEs) is one by one, which is named as sequential scheme. The Virtual MIMO (VMIMO) scheme is that the base station (BS) estimates the DOAs of UEs in a parallel way, which adopts the SA simultaneously. Obviously, when the power is fixed, the VMIMO scheme is much more energy efficient than the sequential scheme. In VMIMO scheme, a set of UEs are grouped together to simultaneously communicate with the BS on a given resource block. Then the BS using multiple antennas can estimate the 2D-DOA of the UEs in the group simultaneously. Based on VMIMO system, the 2D-DOA estimation algorithm for uncorrelated and coherent signals is proposed in this paper. The special structure of mutual coupling matrix (MCM) of uniform linear array (ULA) is applied to eliminate the effect of mutual coupling. The 2D-DOA of uncorrelated signals can be estimated by DOA-matrix method. The parameter pairing between azimuth and elevation is accomplished. Then these estimations are utilized to get the mutual coupling coefficients. Based on spatial smoothing and DOA matrix method, the 2D-DOA of coherent signals can be estimated. The Cramer-Rao lower bound is derived at last. Simulation results demonstrate the effectiveness and performance of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Main memory dynamic voltage and frequency scaling (DVFS) has been proposed recently for improving energy efficiency further. However, recent work overlook the operating systems (OS) problems incurred by it, such as unpredictable performance decreasing, unfair performance sharing and priority inversion, which may render performance analysis, optimization and isolation extremely difficult. In this paper, we analyze the OS problems incurred by memory DVFS in detail firstly, and propose dynamic time-slice scaling (DTS) to address these problems, where allocating each thread a time-slice according to threads' memory accessing behavior and memory frequency. Our paper has three main contributions: 1) we analyze the OS problems incurred by the newly approach of memory active low-power modes, the first work paying attention to the effect of up-to-date DVFS memory architecture; 2) performance decrease is more predictable and share is more fairness through adjusting time-slice; 3) priority inversion is solved with starvation forbidden. Simulation results show that the proposed methods can substantially reduce unpredictable performance degradation, improve fairness of performance sharing and solve the priority inversion. [ABSTRACT FROM AUTHOR]

This paper proposes a secure address configuration protocol for IPv6-based vehicular networks. In this protocol, the network architecture is proposed. In this architecture, a vehicle obtains a unique address from a neighbor vehicle or an access point without DAD, and a leaving vehicle's address space can be automatically reclaimed for reassignment. Based on this architecture, the address configuration algorithm is presented. In this algorithm, an access point or a vehicle owns the unique address space and assigns a unique address to a neighbor vehicle without DAD, so the address configuration cost and delay are lowered. The identification of a vehicle can be authenticated, so the security is achieved. This paper evaluates the performance of this protocol. The data results show that this protocol effectively improves the address configuration performance. [ABSTRACT FROM AUTHOR]

The wireless sensor networks (WSNs) concept was appeared in the middle of 90s and have been a subject under intensive research in the past few years. Several factors have contributed to this, but the potential for application of WSNs in almost every aspect of day-to-day life is the predominant one. This type of networks has been developed using proprietary solutions instead of standard solutions. More recently, the importance of standards motivated the use of IETF standards in WSNs, making the Internet integration easier. However, more efforts are necessary in order to provide a full integration. The WSNs use mainly IPv6 protocol, but the IPv4 is the predominant one in the Internet. As a consequence, IPv4 to IPv6 transition mechanisms must be provided to allow the interaction between all Internet connected devices independently of the supported IP version. It is also critical to provide a standard application interface to make easier the application development and independently of the hardware platform used. The RESTfull Web services can provide this standard interface. So, combine RESTfull Web services with IPv4 to IPv6 transition mechanisms can increase the WSN services dissemination. The transition mechanisms and the REST Web services are supported in the gateway in order to save the wireless sensor device resources'. The smartphone with Internet connectivity can also be the drive to the WSNs growth, because user-friendly applications can be used to retrieve and collect sensed data. This paper proposes a solution based on REST web services to permit the interaction between a mobile application and the IPv6 compliant WSN. [ABSTRACT FROM AUTHOR]

In Wireless Sensor Networks (WSNs), localization is one of the most important technologies since it plays a critical role in many applications, e.g., target tracking. If the users cannot obtain the accurate location information, the related applications cannot be accomplished. The main idea in most localization methods is that some deployed nodes (landmarks) with known coordinates (e.g., GPS-equipped nodes) transmit beacons with their coordinates in order to help other nodes localize themselves. In general, the main localization algorithms are classified into two categories: range-based and range-free. In this paper, we reclassify the localization algorithms with a new perspective based on the mobility state of landmarks and unknown nodes, and present a detailed analysis of the representative localization algorithms. Moreover, we compare the existing localization algorithms and analyze the future research directions for the localization algorithms in WSNs. [ABSTRACT FROM AUTHOR]

Industrial wireless sensor networks (IWSNs) have been widely used in many application scenarios, and data collection is an extremely significant part of IWSNs. Moreover, a mobile sink is widely used in industrial wireless sensor networks to collect sensory data and alleviate the “hot spot” problem effectively. However, usage of a mobile sink introduces some challenges, such as updating of a mobile sink’s location and planning of a mobile sink’s trajectory. Meanwhile, the impact of different distribution types of events on data collection has not been sufficiently valued in designing of data collection algorithm for IWSNs yet. To overcome these challenges, a virtual grid-based real-time data collection algorithm for applications with centrally distributed events (VGDCA-C) is proposed in this paper to gain a reliable data gathering for IWSNs. In the target application scenarios, the events are distributed centrally, so we mainly focus on how to shorten the routing paths and decrease the transmission delay. In our VGDCA-C, a mobile sink can adjust its movement dynamically according to the changes in event areas. The adjustment of a mobile sink movement strategy includes two aspects. The first one is the dynamic adjustment of a mobile sink’s parking time, and the second one denotes the moving toward event area of a mobile sink. Thus, a mobile sink adjusts its location such that it can get closer to the event area. Hence, the total length of routing is getting shorter so that source nodes can upload sensory data faster. Analysis and simulation results show that compared with the existing work, our VGDCA-C increases the network lifetime and decreases transmission delay. [ABSTRACT FROM AUTHOR]

Recently, Pt-Y alloy has displayed an excellent electrocatalytic activity for oxygen reduction reaction (ORR), and is regarded as a promising cathode catalyst for fuel cells. However, the bulk production of nanoscaled Pt-Y alloy with outstanding catalytic performance remains a great challenge. Here, we address the challenge through a simple dealloying method to synthesize nanoporous Pt-Y alloy (NP-PtY) with a typical ligament size of ~5 nm. By combining the intrinsic superior electrocatalytic activity of Pt-Y alloy with the special nanoporous structure, the NP-PtY bimetallic catalyst presents higher activity for ORR and ethanol oxidation reaction, and better electrocatalytic stability than the commercial Pt/C catalyst and nanoporous Pt alloy. The as-made NP-PtY holds great application potential as a promising electrocatalyst in proton exchange membrane fuel cells due to the advantages of facile preparation and excellent catalytic performance. [ABSTRACT FROM AUTHOR]

With the rapid development of industrial IoT technology, a growing number of intelligent devices are being deployed in smart factories to digitally upgrade the manufacturing industry. The increasing number of intelligent devices brings a huge task request. Fog computing, which is an emerging distributed computing paradigm, is widely applied to process the device data generated in smart manufacturing. However, as fog nodes are resource limited and geographically widely distributed limitations, proper fog node placement strategies are critical to enhance the service performance of fog computing systems. In this paper, we study the problem of fog node placement in smart factories and divide it into two scenarios, fixed device and mobile device fog node placement, depending on the mobility of the devices. The fog node placement model and objective function are built in the two scenarios, and two improved heuristic algorithms are proposed to obtain the most optimal placement scheme. In addition, we perform simulation experiments based on existing intelligent production line prototype platforms and devices to evaluate the performance of the proposed algorithms. The IGA reduces latency by an average of 586.7-1089ms\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$586.7 - 1089{\text{ms}}$$\end{document} over the benchmark algorithm, saving 18.3-39%\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$18.3 - 39\%$$\end{document} in energy consumption. The total latency of IMOA is reduced by 59.8-68.5%\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$59.8 - 68.5\%$$\end{document}, and the maximum latency is reduced by 48.8-69.2%\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$48.8 - 69.2\%$$\end{document}. The experimental results show that the proposed algorithms outperform other benchmark algorithms in terms of task response time and energy consumption. [ABSTRACT FROM AUTHOR]