A Bilevel Optimization Approach for Joint Offloading Decision and Resource Allocation in Cooperative Mobile Edge Computing

This paper studies a multi-user cooperative mobile edge computing offloading (CoMECO) system in a multi-user interference environment, in which delay-sensitive tasks may be executed on local devices, cooperative devices, or the primary MEC server. In this system, we jointly optimize the offloading decision and computation resource allocation for minimizing the total energy consumption of all mobile users under the delay constraint. If this problem is solved directly, the offloading decision and computation resource allocation are generally generated separately at the same time. Note, however, that they are closely coupled. Therefore, under this condition, their dependency is not well considered, thus leading to poor performance. We transform this problem into a bilevel optimization problem, in which the offloading decision is generated in the upper level, and then the optimal allocation of computation resources is obtained in the lower level based on the given offloading decision. In this way, the dependency between the offloading decision and computation resource allocation can be fully taken into account. Subsequently, a bilevel optimization approach, called BiJOR, is proposed. In BiJOR, candidate modes are first pruned to reduce the number of infeasible offloading decisions. Afterward, the upper level optimization problem is solved by ant colony system (ACS). Furthermore, a sorting strategy is incorporated into ACS to construct feasible offloading decisions with a higher probability and a local search operator is designed in ACS to accelerate the convergence. For the lower level optimization problem, it is solved by the monotonic optimization method. In addition, BiJOR is extended to deal with a complex scenario with the channel selection. Extensive experiments are carried out to investigate the performance of BiJOR on two sets of instances with up to 400 mobile users. The experimental results demonstrate the effectiveness of BiJOR and the superiority of the CoMECO system

An R

An R2 indicator based selection method is a major ingredient in the formulation of indicator based evolutionary multiobjective optimization algorithms. The existing classical indicator based selection methodologies have demonstrated an excellent performance to solve low-dimensional optimization problems. However, the R2 indicator based evolutionary multiobjective optimization algorithms encounter enormous challenges in high-dimensional objective space. Our main purpose is to explore how to extend the R2 indicator to handle many-objective optimization problems. After analyzing the R2 indicator, the objective space partition strategy, and the decomposition method, we propose a steady-state evolutionary algorithm based on the R2 indicator and the decomposition method, named, R2-MOEA/D, to obtain well-converged and well-distributed Pareto front. The main contribution of this paper contains two aspects. (1) The convergence and diversity for the R2 indicator based selection are analyzed. Two improper selection situations will be properly solved via applying the decomposition method. (2) According to the position of a new individual in the steady-state evolutionary algorithm, two different objective space partition strategies and the corresponding selection methods are proposed. Extensive experiments are conducted on a variety of benchmark test problems, and the experimental results demonstrate that the proposed algorithm has competitive performance in comparison with several tailored algorithms for many-objective optimization

Sequence alignment and conserved domain analysis of GhGLIP.

<p>Four conserved blocks of I, II, III and V were boxed. The typical GDS(L) sequence is indicated with a double line. The N-terminal signal peptide and transmembrane helix are displayed with solid and dashed lines respectively. The symbols asterisks (*), triangles () and pounds (#) represent the plant SGNH-lipase conserved active sites residues, Ser-His-Asp(Glu) catalytic triad and oxyanion hole respectively. The aligned proteins are listed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0195556#pone.0195556.s004" target="_blank">S2 Table</a>.</p

Hypolipidemic effects of chitosan and its derivatives in hyperlipidemic rats induced by a high-fat diet

Background: Hyperlipidemia (HLP) is the primary risk factor of cardiovascular disease (CVD). Various factors, including genetics, physical inactivity, and daily nutritional habits, affect the prevalence of HLP. Recently, it was revealed that dietary fibers, such as pectin, psyllium, and especially chitosan (CTS), may play important roles in hypolipidemic management. Thus, this study aims to determine the hypolipidemic effect and mechanism of CTS and its water-soluble derivatives, chitosan oligosaccharides (MN≤1,000 Da (COSI) and MN≤3,000 Da (COSIII)), in male hyperlipidemic rats induced by a high-fat diet (HFD). Design: After the model creation, 120 Sprague-Dawley (SD) rats were equally assigned to 12 groups fed various diets as follows: the normal group with basic diet, an HFD group, an HFD group supplemented with three doses of CTS, COSI and COSIII groups, and an HFD group treated with simvastatin (7 mg/kg·d). After 6 weeks, body weight, fat/body ratio, and the relevant biomarkers of serum, liver, and feces were measured. Additionally, the histological analysis of liver and adipose tissue was performed, and the mRNA expressions of liver peroxisome proliferator-activated receptor-α (PPARα) and hepatic lipase (HL) were examined. Results: Compared with HFD group, rats fed CTS, COSI, and COSIII showed a better ability to regulate their body weight, liver and cardiac indices, fat/body ratio, as well as serum, liver, and fecal lipids, and simultaneously to maintain the appropriate activity of liver and serum superoxide dismutase (SOD), alanine aminotransferase (ALT), aspartate aminotransferase (AST), as well as liver and fecal total bile acids (TBA). Simultaneously, there had been a higher mRNA expression of PPARα and HL in the treatment groups. Conclusion: The obtained results suggested that these three function foods can effectively improve liver lipid metabolism by normalizing the expressions of PPARα and HL, and protect liver from the oxidized trauma by enhancing hepatic function, which could be potentially used to remedy hyperlipidemia

Anti-Obese Effect of Glucosamine and Chitosan Oligosaccharide in High-Fat Diet-Induced Obese Rats

Objective: This study is to evaluate the anti-obese effects of glucosamine (GLC) and chitosan oligosaccharide (COS) on high-fat diet-induced obese rats. Methods: The rats were randomly divided into twelve groups: a normal diet group (NF), a high-fat diet group (HF), Orlistat group, GLC high-, middle-, and low-dose groups (GLC-H, GLC-M, GLC-L), COS1 (COS, number-average molecular weight ≤1000) high-, middle-, and low-dose groups (COS1-H, COS1-M, COS1-L), and COS2 (COS, number-average molecular weight ≤3000) high-, middle-, and low-dose groups (COS2-H, COS2-M, COS2-L). All groups received oral treatment by gavage once daily for a period of six weeks. Results: Rats fed with COS1 gained the least weight among all the groups (P &lt; 0.01), and these rats lost more weight than those treated with Orlistat. In addition to the COS2-H and Orlistat groups, the serum total cholesterol (CHO) and low-density lipoprotein cholesterol (LDL-C) levels were significantly reduced in all treatment groups compared to the HF group (P &lt; 0.01). The various doses of GLC, COS1 and COS2 reduced the expression levels of PPARγ and LXRα mRNA in the white adipose tissue. Conclusions: The results above demonstrated that GLC, COS1, and COS2 improved dyslipidemia and prevented body weight gains by inhibiting the adipocyte differentiation in obese rats induced by a high-fat diet. Thus, these agents may potentially be used to treat obesity