Joint Data compression and Computation offloading in Hierarchical Fog-Cloud Systems

Data compression has the potential to significantly improve the computation offloading performance in hierarchical fog-cloud systems. However, it remains unknown how to optimally determine the compression ratio jointly with the computation offloading decisions and the resource allocation. This joint optimization problem is studied in the current paper where we aim to minimize the maximum weighted energy and service delay cost (WEDC) of all users. First, we consider a scenario where data compression is performed only at the mobile users. We prove that the optimal offloading decisions have a threshold structure. Moreover, a novel three-step approach employing convexification techniques is developed to optimize the compression ratios and the resource allocation. Then, we address the more general design where data compression is performed at both the mobile users and the fog server. We propose three efficient algorithms to overcome the strong coupling between the offloading decisions and resource allocation. We show that the proposed optimal algorithm for data compression at only the mobile users can reduce the WEDC by a few hundred percent compared to computation offloading strategies that do not leverage data compression or use sub-optimal optimization approaches. Besides, the proposed algorithms for additional data compression at the fog server can further reduce the WEDC

Computation Offloading and Resource Allocation for Backhaul Limited Cooperative MEC Systems

In this paper, we jointly optimize computation offloading and resource allocation to minimize the weighted sum of energy consumption of all mobile users in a backhaul limited cooperative MEC system with multiple fog servers. Considering the partial offloading strategy and TDMA transmission at each base station, the underlying optimization problem with constraints on maximum task latency and limited computation resource at mobile users and fog servers is non-convex. We propose to convexify the problem exploiting the relationship among some optimization variables from which an optimal algorithm is proposed to solve the resulting problem. We then present numerical results to demonstrate the significant gains of our proposed design compared to conventional designs without exploiting cooperation among fog servers and a greedy algorithm

Economic Instruments and the Pollution Impact of the 2006-2010 Vietnam Socio-Economic Development Plan

The current study derives optimal growth paths for pollution emission charges, in order to control future water pollution emissions in the Vietnamese manufacturing sector. The study builds on a prior study, which estimated the manufacturing sector pollution impact of the 2006- 2010 SEDP development plan for Vietnam (Jensen et al.; 2008). The current study demonstrates that effective implementation and moderate expansion of optimal emission charges, under certain conditions, could have been used, as part of the 2006-2010 SEDP development plan, to control pollution emissions at 2005 levels. Moreover, such a scenario would have been accompanied by a moderate expansion in fiscal revenues and a relatively minor economy-wide efficiency loss. The current study, therefore, suggests that effective implementation and gradual expansion of pollution emission charges should be incorporated into future SEDP development plans, in order to control pollution emissions as development progresses in Vietnam.Vietnam, manufacturing, CGE

Investigating the elements influencing the psychological issues of reform school students

Reformatory students are those whose deviant behaviors and habits prevent them from receiving education under normal educational conditions. These students frequently lead a careless, undisciplined lifestyle, being unwilling to work and learn eager to play and demanding. Therefore, when they are admitted to reformatories with severe study and lifestyle requirements, they have great psychological difficulty adjusting to their new environment. Students’ psychological issues in adapting to reformatory learning and living regimes are difficult and psychological deficits make it challenging for students to adapt to reformatory learning and living conditions. In Vietnam, 665 students from reformatory schools were polled to determine the causes of psychological issues. According to the findings, a variety of elements contribute to students’ psychological difficulties. Individual student conditions such as health, awareness, attitudes and actions as well as inappropriate habits, living without goals or aspirations, etc. are on the subjective side of the equation. On the objective side are the students’ conditions, family, education and psychological obstacles brought on by less-than-ideal circumstances which will make it more difficult for community students to adapt. Both the new school and society must pay more attention to reformatory students in order to establish the conditions necessary for successful integration into the new school and ultimate readmission into society for these students

A Robust Mobile Robot Navigation System using Neuro-Fuzzy Kalman Filtering and Optimal Fusion of Behavior-based Fuzzy Controllers

This study proposes a control system model for mobile robots navigating in unknown environments. The proposed model includes a neuro-fuzzy Extended Kalman Filter for localization task and a behaviorbased fuzzy multi-controller navigation module. The neuro-fuzzy EKF, used for estimating the robot’s position from sensor readings, is an enhanced EKF whose noise covariance matrix is progressively adjusted by a fuzzy neural network. The navigation module features a series of independently-executed fuzzy controllers, each deals with a specific navigation sub-task, or behavior, and a multi-objective optimizer to coordinate all behaviors. The membership functions of all fuzzy controllers play the roles of objective functions for the optimizer, which produces an overall Pareto-optimal control signal to drive the robot. A number of simulations and real-world experiments were conducted to evaluate the performance of this model

Fair Resource Allocation for OFDMA Femtocell Networks With Macrocell Protection

We consider the joint subchannel allocation and power control problem for orthogonal frequency-division multiple-access (OFDMA) femtocell networks in this paper. Specifically, we are interested in the fair resource-sharing solution for users in each femtocell that maximizes the total minimum spectral efficiency of all femtocells subject to protection constraints for the prioritized macro users. Toward this end, we present the mathematical formulation for the uplink resource-allocation problem and propose an optimal exhaustive search algorithm. Given the exponential complexity of the optimal algorithm, we develop a distributed and low-complexity algorithm to find an efficient solution for the problem. We prove that the proposed algorithm converges and we analyze its complexity. Then, we extend the proposed algorithm in three different directions, namely, downlink context, resource allocation with rate adaption for femto users, and consideration of a hybrid access strategy where some macro users are allowed to connect with nearby femto base stations (FBSs) to improve the performance of the femto tier. Finally, numerical results are presented to demonstrate the desirable performance of the proposed algorithms

Genetic landscape of autism spectrum disorder in Vietnamese children

Autism spectrum disorder (ASD) is a complex disorder with an unclear aetiology and an estimated global prevalence of 1%. However, studies of ASD in the Vietnamese population are limited. Here, we first conducted whole exome sequencing (WES) of 100 children with ASD and their unaffected parents. Our stringent analysis pipeline was able to detect 18 unique variants (8 de novo and 10 ×-linked, all validated), including 12 newly discovered variants. Interestingly, a notable number of X-linked variants were detected (56%), and all of them were found in affected males but not in affected females. We uncovered 17 genes from our ASD cohort in which CHD8, DYRK1A, GRIN2B, SCN2A, OFD1 and MDB5 have been previously identified as ASD risk genes, suggesting the universal aetiology of ASD for these genes. In addition, we identified six genes that have not been previously reported in any autism database: CHM, ENPP1, IGF1, LAS1L, SYP and TBX22. Gene ontology and phenotype-genotype analysis suggested that variants in IGF1, SYP and LAS1L could plausibly confer risk for ASD. Taken together, this study adds to the genetic heterogeneity of ASD and is the first report elucidating the genetic landscape of ASD in Vietnamese children