Journal of Telecommunications and Information Technology, Load Balancing Based on Optimization Algorithms: An Overview, 2019, nr 4

Combinatorial optimization challenges are rooted in real-life problems, continuous optimization problems, discrete optimization problems and other significant problems in telecommunications which include, for example, routing, design of communication networks and load balancing. Load balancing applies to distributed systems and is used for managing web clusters. It allows to forward the load between web servers, using several scheduling algorithms. The main motivation for the study is the fact that combinatorial optimization problems can be solved by applying optimization algorithms. These algorithms include ant colony optimization (ACO), honey bee (HB) and multi-objective optimization (MOO). ACO and HB algorithms are inspired by the foraging behavior of ants and bees which use the process to locate and gather food. However, these two algorithms have been suggested to handle optimization problems with a single-objective. In this context, ACO and HB have to be adjusted to multiobjective optimization problems. This paper provides a summary of the surveyed optimization algorithms and discusses the adaptations of these three algorithms. This is pursued by a detailed analysis and a comparison of three major scheduling techniques mentioned above, as well as three other, new algorithms (resulting from the combination of the aforementioned techniques) used to efficiently handle load balancing issue

BADANIA REDUKCJI OPÓŹNIEŃ SERWERA WWW

This paper investigates the characteristics of web server response delay in order to understand and analyze the optimization techniques of reducing latency. The analysis of the latency behavior for multi-process Apache HTTP server with different thread count and various workloads, was made. It was indicated, that the insufficient number of threads used by the server handling the concurrent requests of clients, is responsible for increasing latency under various loads. The problem can be solved by using a modified web server configuration allowing to reduce the response time.W artykule opisano badania charakterystyk czasowych serwera WWW w celu zrozumienia i analizy technik optymalizacyjnych powodujących redukcję opóźnienia. Dokonano analizy czasów opóźnień dla wieloprocesowego serwera Apache dla różnej liczby wątków i obciążeń. Wskazano, że niewystarczająca liczba wątków wykorzystywanych przez serwer, obsługujących jednoczesne żądania klientów, wpływa znacząco na zwiększenie opóźnień dla różnych obciążeń. Problem może być rozwiązany za pomocą modyfikacji ustawień serwera WWW, pozwalających na skrócenie czasu reakcji

Short and Long-Term Effect of Land Use and Management on Soil Organic Carbon Stock in Semi-Desert Areas of North Africa-Tunisia

Soil organic carbon (SOC) plays an important role in the global C cycle, as well as in the maintenance and improvement of the soil quality. Over time, special attention has been paid to it in the study of the SOC reserves worldwide; however, reduced attention has been given to assessing the spatial patterns of SOC stock (SOCS) in semi-desert ecosystems. In this line, there are no conclusive studies in drylands of Africa affected by aeolian processes (semi-desert conditions) mainly due to the complexity of sample collection, and this is especially significant in some soil types such as Arenosols (AR) and Calcisols (CL). This study evaluated the spatial variability of SOC and SOCS in AR and CL with woody crops in relation to land use and management (old plantations > 100 years: centenary olive grove; new plantations < 12 years: young olive grove, almond, and pistachio) in semi-desert conditions. For this purpose, 16 soil profiles (for 0–40 and 40–100 cm depth) were selected and studied in an experimental area of Menzel Chaker-Sfax in southeastern Tunisia (North Africa). The main results indicated that the SOCS on average was higher in Old Cultivated AR (OC-AR) with 41.16 Mg ha−1 compared to Newly Cultivated AR (NC-AR) with 25.13 Mg ha−1. However, the SOCS decreased after a long period of cultivation in CL from 43.00 Mg ha−1 (Newly Cultivated CL: NC-CL) to 32.19 Mg ha−1 (Old Cultivated CL: OC-CL). This indicates that in the long term, CL has more capacity to store SOC than AR, and that in the short term, AR is more sensitive to land management than CL

A load balancing system to protect servers against DDoS attacks

A Distributed Denial of Service (DDoS) aims at shutting down the services of intended servers with over-consumption of bandwidth or CPU processor and memory units, and considers the one of the hardest security problems in today's Internet. In this context, load balancing allows to distribute workloads among the processors, which provides a high protection in local area network (LAN) because it improves the quality of service and the performance. In this paper, we intend to present a load balancing system which is based on various algorithms and has as a main role to mitigate the impact of DDoS attacks

Hybrid Nearest-Neighbor Ant Colony Optimization Algorithm for Enhancing Load Balancing Task Management

Many computer problems that arise from real-world circumstances are NP-hard, while, in the worst case, these problems are generally assumed to be intractable. Existing distributed computing systems are commonly used for a range of large-scale complex problems, adding advantages to many areas of research. Dynamic load balancing is feasible in distributed computing systems since it is a significant key to maintaining stability of heterogeneous distributed computing systems (HDCS). The challenge of load balancing is an objective function of optimization with exponential complexity of solutions. The problem of dynamic load balancing raises with the scale of the HDCS and it is hard to tackle effectively. The solution to this unsolvable issue is being explored under a particular algorithm paradigm. A new codification strategy, namely hybrid nearest-neighbor ant colony optimization (ACO-NN), which, based on the metaheuristic ant colony optimization (ACO) and an approximate nearest-neighbor (NN) approaches, has been developed to establish a dynamic load balancing algorithm for distributed systems. Several experiments have been conducted to explore the efficiency of this stochastic iterative load balancing algorithm; it is tested with task and nodes accessibility and proved to be effective with diverse performance metrics

Performance evaluation of multi-protocol label switching (MPLS) over IP

Networks have evolved in terms of infrastructure and configuration incorporating new technologies and adapting them to take account of the need for technicality and compatibility with the rapid changes taking place in the world. MPLS (Multi Protocol Label Switching) is a versatile solution (based on QoS) to solve the problems addressed by the present networks like IP (Internet Protocol). In this chapter, we evaluate IP /MPLS networks in terms of performance, using several criteria of QoS. These criteria include: delay variation (average delay and delay), through put and loss rates. We evaluate through several types of flow (data, voice, video). To simulate IP/MPLS topology, we use the NS-2 simulator

Load Balancing Based on Optimization Algorithms: An Overview

Combinatorial optimization challenges are rooted in real-life problems, continuous optimization problems, discrete optimization problems and other significant problems in telecommunications which include, for example, routing, design of communication networks and load balancing. Load balancing applies to distributed systems and is used for managing web clusters. It allows to forward the load between web servers, using several scheduling algorithms. The main motivation for the study is the fact that combinatorial optimization problems can be solved by applying optimization algorithms. These algorithms include ant colony optimization (ACO), honey bee (HB) and multi-objective optimization (MOO). ACO and HB algorithms are inspired by the foraging behavior of ants and bees which use the process to locate and gather food. However, these two algorithms have been suggested to handle optimization problems with a single-objective. In this context, ACO and HB have to be adjusted to multiobjective optimization problems. This paper provides a summary of the surveyed optimization algorithms and discusses the adaptations of these three algorithms. This is pursued by a detailed analysis and a comparison of three major scheduling techniques mentioned above, as well as three other, new algorithms (resulting from the combination of the aforementioned techniques) used to efficiently handle load balancing issues

Insights into the Synthesis Parameters Effects on the Structural, Morphological, and Magnetic Properties of Copper Oxide Nanoparticles

The present study aims at the integration of the &ldquo;oxalic conversion&rdquo; route into &ldquo;green chemistry&rdquo; for the synthesis of copper oxide nanoparticles (CuO-NPs) with controllable structural, morphological, and magnetic properties. Two oxalate-containing precursors (H2C2O4.2H2O and (NH4)2C2O4.H2O) and different volume ratios of a mixed water/glycerol solvent were tested. First, the copper oxalates were synthesized and then subjected to thermal decomposition in air at 400 &deg;C to produce the CuO powders. The purity of the samples was confirmed by X-ray powder diffraction (XRPD), and the crystallite sizes were calculated using the Scherrer method. The transmission electron microscopy (TEM) images revealed oval-shaped CuO-NPs, and the scanning electron microscopy (SEM) showed that morphological features of copper oxalate precursors and their corresponding oxides were affected by the glycerol (V/V) ratio as well as the type of C2O42&minus; starting material. The magnetic properties of CuO-NPs were determined by measuring the temperature-dependent magnetization and the hysteresis curves at 5 and 300 K. The obtained results indicate the simultaneous coexistence of dominant antiferromagnetic and weak ferromagnetic behavior

Inhibitory Activities of Zygophyllum album: A Natural Weight-Lowering Plant on Key Enzymes in High-Fat Diet-Fed Rats

Obesity is a serious health problem that increased risk for many complications, including diabetes and cardiovascular disease. The results showed EZA, which found rich in flavonoids and phenolic compounds, exhibited an inhibitory activity on pancreatic lipase in vitro with IC50 of 91.07 μg/mL. In vivo administration of this extract to HFD-rats lowered body weight and serum leptin level; and inhibited lipase activity of obese rats by 37% leading to notable decrease of T-Ch, TGs and LDL-c levels accompanied with an increase in HDL-c concentration in serum and liver of EZA treated HFD-rats. Moreover, the findings revealed that EZA helped to protect liver tissue from the appearance of fatty cysts. Interestingly, supplementation of EZA modulated key enzyme related to hypertension such as ACE by 36% in serum of HFD animals and improve some of serum electrolytes such as Na+, K+, Cl−, Ca2+ and Mg2+. Moreover, EZA significantly protected the liver-kidney function by reverted back near to normal the values of the liver-kidney dysfunction indices AST&ALT, ALP, CPK and GGT activities, decreased T-Bili, creat, urea and uric acid rates. In conclusion, these results showed a strong antihypelipidemic effect of EZA which can delay the occurrence of dislipidemia and hypertension