Towards Optimal Distributed Node Scheduling in a Multihop Wireless Network through Local Voting

In a multihop wireless network, it is crucial but challenging to schedule transmissions in an efficient and fair manner. In this paper, a novel distributed node scheduling algorithm, called Local Voting, is proposed. This algorithm tries to semi-equalize the load (defined as the ratio of the queue length over the number of allocated slots) through slot reallocation based on local information exchange. The algorithm stems from the finding that the shortest delivery time or delay is obtained when the load is semi-equalized throughout the network. In addition, we prove that, with Local Voting, the network system converges asymptotically towards the optimal scheduling. Moreover, through extensive simulations, the performance of Local Voting is further investigated in comparison with several representative scheduling algorithms from the literature. Simulation results show that the proposed algorithm achieves better performance than the other distributed algorithms in terms of average delay, maximum delay, and fairness. Despite being distributed, the performance of Local Voting is also found to be very close to a centralized algorithm that is deemed to have the optimal performance

Consensus-based Distributed Algorithm for Multisensor-Multitarget Tracking under Unknown–but–Bounded Disturbances

We consider a dynamic network of sensors that cooperate to estimate parameters of multiple targets. Each sensor can observe parameters of a few targets, reconstructing the trajectories of the remaining targets via interactions with “neighbouring” sensors. The multi-target tracking has to be provided in the face of uncertainties, which include unknown-but-bounded drift of parameters, noise in observations and distortions introduced by communication channels. To provide tracking in presence of these uncertainties, we employ a distributed algorithm, being an “offspring” of a consensus protocol and the stochastic gradient descent. The mathematical results on the algorithm’s convergence are illustrated by numerical simulations

Differentiated consensuses in a stochastic network with priorities,”

Abstract-In this paper a distributed stochastic network system with incoming tasks that are classified with priorities is studied. The network system is assumed to have variable topology, and agents are not necessarily always connected to each other. In addition, the observations about neighbors' states are supposed to be obtained with random noise and delays. To ensure efficient operation of this network system, a novel control strategy is proposed. With this strategy, network resources are allocated in a randomized way with probabilities corresponding to each priority class. To maintain the balanced load across the network for different priorities, a so-called "differentiated consensuses" problem is examined. This consensus problem is that, in a system with multiple classes, consensus is targeted for each class, which may be different among classes. In this paper, the ability of the proposed control protocol to maintain almost balanced load, i.e. approximate consensus for every priority class across the network, is proved. In addition, a numerical example that illustrates the proposed control strategy and the results of simulations are provided

Knowledge transfer of eLearning objects: Lessons learned from an intercontinental capacity building project

Background Effective knowledge transfer of eLearning objects can hasten the adoption and dissemination of technology in teaching and learning. However, challenges exist which hinder inter-organisational knowledge transfer, particularly across continents. The ACoRD project aimed to transfer knowledge on digital learning development from UK/EU (provider) to Malaysian (receiver) higher education institutions (HEIs). This study explores the challenges encountered during the knowledge transfer process and lessons learned. Methods This is a qualitative study involving both the knowledge providers and receivers in focus group discussions (n = 25). Four focus group discussions were conducted in the early (n = 2) and mid-phase (n = 2) of the project by trained qualitative researchers using a topic guide designed to explore experiences and activities representing knowledge transfer in multi-institutional and multi-cultural settings. The interviews were audio-recorded, transcribed verbatim, and checked. The transcripts were analysed using thematic analysis. Results Five main themes emerged from this qualitative study: mismatched expectations between providers and receivers; acquiring new knowledge beyond the professional "comfort zone"; challenges in cascading newly acquired knowledge to colleagues and management; individual and organisational cultural differences; and disruption of knowledge transfer during the COVID-19 pandemic. Conclusion This study highlights the need to create a conducive platform to facilitate continuous, timely and bi-directional needs assessment and feedback; this should be done in the early phase of the knowledge transfer process. The challenges and strategies identified in this study could guide more effective knowledge transfer between organisations and countries.publishedVersio

Prioritising topics for developing e-learning resources in healthcare curricula: A comparison between students and educators using a modified Delphi survey

Background Engaging students in the e-learning development process enhances the effective implementation of e-learning, however, students’ priority on the topics for e-learning may differ from that of the educators. This study aims to compare the differences between the students and their educators in prioritising the topics in three healthcare curricula for reusable e-learning object (RLO) development. Method A modified Delphi study was conducted among students and educators from University Malaya (UM), Universiti Putra Malaysia (UPM) and Taylor’s University (TU) on three undergraduate programmes. In Round 1, participants were asked to select the topics from the respective syllabi to be developed into RLOs. Priority ranking was determined by using frequencies and proportions. The first quartile of the prioritised topics was included in Round 2 survey, which the participants were asked to rate the level of priority of each topic using a 5-point Likert scale. The mean score of the topics was compared between students and educators. Result A total of 43 educators and 377 students participated in this study. For UM and TU Pharmacy, there was a mismatch in the prioritised topics between the students and educators. For UPM, both the educators and students have prioritised the same topics in both rounds. To harmonise the prioritisation of topics between students and educators for UM and TU Pharmacy, the topics with a higher mean score by both the students and educators were prioritised. Conclusion The mismatch in prioritised topics between students and educators uncovered factors that might influence the prioritisation process. This study highlighted the importance of conducting needs assessment at the beginning of eLearning resources development.publishedVersio

Prioritising topics for developing e-learning resources in healthcare curricula: A comparison between students and educators using a modified Delphi survey

Background Engaging students in the e-learning development process enhances the effective implementation of e-learning, however, students’ priority on the topics for e-learning may differ from that of the educators. This study aims to compare the differences between the students and their educators in prioritising the topics in three healthcare curricula for reusable e-learning object (RLO) development. Method A modified Delphi study was conducted among students and educators from University Malaya (UM), Universiti Putra Malaysia (UPM) and Taylor’s University (TU) on three undergraduate programmes. In Round 1, participants were asked to select the topics from the respective syllabi to be developed into RLOs. Priority ranking was determined by using frequencies and proportions. The first quartile of the prioritised topics was included in Round 2 survey, which the participants were asked to rate the level of priority of each topic using a 5-point Likert scale. The mean score of the topics was compared between students and educators. Result A total of 43 educators and 377 students participated in this study. For UM and TU Pharmacy, there was a mismatch in the prioritised topics between the students and educators. For UPM, both the educators and students have prioritised the same topics in both rounds. To harmonise the prioritisation of topics between students and educators for UM and TU Pharmacy, the topics with a higher mean score by both the students and educators were prioritised. Conclusion The mismatch in prioritised topics between students and educators uncovered factors that might influence the prioritisation process. This study highlighted the importance of conducting needs assessment at the beginning of eLearning resources development

Combined Procedure with Randomized Controls for the Parameters' Confidence Region of Linear Plant under External Arbitrary Noise

Abstract-The new algorithm is proposed for the estimating of linear plant's unknown parameters in the case of observations with arbitrary external noises. It is based on adding of randomized inputs (test perturbations) through the feedback channel. The assumptions about the noise are reduced to a minimum: it can virtually be arbitrary but independently of it the user must be able to add test perturbations. We combine the previous result about asymptotic properties of randomized control strategy with the new one which is followed by a nonasymptotic approach of LSCR (Leave-out Sign-dominant Correlation Regions) method. The new algorithm gives confidence regions for series of finite sets of observations. These regions shrink to the true values of an unknown parameters when number of observations tents to infinity while the algorithm complexity does not increases

Local voting protocol step-size choice for consensus achievement

In the paper, a multi-agent network system of different computing nodes is considered. A problem of load balancing in the network is addressed. The problem is formulated as consensus achievement problem and solved via local voting protocol. Agents exchange information about their states in presence of noise in communication channels. For the system operating in noised conditions analytically obtained estimation of control protocol optimal step size value is given. The dependence of the system behaviour on value of control protocol step-size is demonstrated in simulation examples