The massive deployment of small cell Base Stations (SBSs) empowered with computing capabilities presents one of the most ingenious solutions adopted for 5G cellular networks towards meeting the foreseen data explosion and the ultra-low latency demanded by mobile applications. This empowerment of SBSs with Multi-access Edge Computing (MEC) has emerged as a tentative solution to overcome the latency demands and bandwidth consumption required by mobile applications at the network edge. The MEC paradigm offers a limited amount of resources to support computation, thus mandating the use of intelligence mechanisms for resource allocation. The use of green energy for powering the network apparatuses (e.g., Base Stations (BSs), MEC servers) has attracted attention towards minimizing the carbon footprint and network operational costs. However, due to their high intermittency and unpredictability, the adoption of learning methods is a requisite. Towards intelligent edge system management, this paper proposes a Green-based Edge Network Management (GENM) algorithm, which is a online edge system management algorithm for enabling green-based load balancing in BSs and energy savings within the MEC server. The main goal is to minimize the overall energy consumption and guarantee the Quality of Service (QoS) within the network. To achieve this, the GENM algorithm performs dynamic management of BSs, autoscaling and reconfiguration of the computing resources, and on/off switching of the fast tunable laser drivers coupled with location-aware traffic scheduling in the MEC server. The obtained simulation results validate our analysis and demonstrate the superior performance of GENM compared to a benchmark algorithm.
Load balancing between adjacent base stations (BSs) is important for balancing load distributions and improving service provisioning. Whilst load balancing between any given pair of BSs is beneficial, cascade load sharing can cause network level instability that is hard to predict. The relationship between each BS's load balancing dynamics and the network topology is not understood. In this seminal work on stability analysis, we consider a frequency re-use network with no interference, whereby load balancing dynamics doesn't perturb the individual cells' capacity. Our novelty is to show an exa…
This paper explains the enhancement of handover processes in GSM networks by using Load balancing algorithms (Round Robin), comparing the results with the real system to determine the improvement percentage.
The load-balancing system, built on the basis of a subsystem load balancer and subsystem control and monitoring that closely interact with each other was propose in work. This system is presented as a queuing system with priority service discipline. In the described queuing system parallel processing flow applications occur in the multiple serving devices and successive junction of them into unified stream is done. The method of multifractal load balancing is submited on the basis of the developed system of load balancing.
In this paper, the problem of load balancing in network intrusion detection system is considered. Load balancing method based on work of several components of network intrusion detection system and on the analysis of multifractal properties of incoming traffic is proposed. The proposed method takes into account a degree of multifractality for calculation of deep packet inspection time, on the basis of which the time necessary for comparing the packet with the signatures is calculated. Load balancing rules are generated using the estimated average deep packet inspection time and the multifracta…
Data center networks need load balancing mechanisms to dynamically serve a large number of flows with different service requirements. However, traditional load-balancing approaches do not allow the full utilization of network resources in a simple, programmable, and scalable way. In this context, this paper proposes RDNA Balance that exploits elephant flow isolation and source routing in core nodes. Flow classification operations are performed on the edge using features of the OpenFlow protocol. The results show that with this approach it is possible to provide a simple, scalable, and programm…
The dynamic load balancing algorithm based on the monitoring server load, self-similar characteristics of passing traffic have to provide a statistically uniform load distribution on servers, high performance, fault tolerance and capacity, low response time, the amount of overhead and losses was propose in work. Integrated measurement for the total imbalance level of the system were entered.
In order to utilize network resources and provide a more reliable delivery of information, multipath routing algorithms are used with a higher priority than single path routing. But providing the quality of service (QoS) requirements while load balancing is done among multiple paths is still a challenge. In this paper a new load balancing algorithm is proposed by using an explicit endpoint admission control (EEAC) to achieve a dynamic load balancing algorithm, with the ability to guarantee the end-to-end QoS for a variety of service classes. The simulation results for non deterministic network…
The classification of the most used load balancing algorithms in distributed systems (including cloud technology, cluster systems, grid systems) is described. Comparative analysis of types of the load balancing algorithms is conducted in accordance with the classification, the advantages and drawbags of each type of the algorithms are shown. Performance indicators characterizing each algorithm are indicated.
In the load balancing problem, each node in a network is assigned a load, and the goal is to equally distribute the loads among the nodes, by preforming local load exchanges. While load balancing was extensively studied in static networks, only recently a load balancing algorithm for dynamic networks with a bounded convergence time was presented. In this paper, we further study the time complexity of load balancing in the context of dynamic networks. First, we show that randomness is not necessary, and present a deterministic algorithm which slightly improves the running time of the previous a…
Recently, fog computing has been introduced as a modern distributed paradigm and complement to cloud computing to provide services. Fog system extends storing and computing to the edge of the network, which can solve the problem about service computing of the delay-sensitive applications remarkably besides enabling the location awareness and mobility support. Load balancing is an important aspect of fog networks that avoids a situation with some under-loaded or overloaded fog nodes. Quality of Service (QoS) parameters such as resource utilization, throughput, cost, response time, performance, …
Recent exponential growth of data over cellular networks has cause the progression from conventional mobile communication networks to heterogeneous cellular networks (HetNets). Quality of experience (QoE)-aware traffic load balancing in such dense HetNets is considered a major problem. Current HetNets exploit reactive load balancing schemes that hinder in achieving desired QoE gain. In this paper, we propose a novel proactive load balancing framework which leverages content caching and mobility prediction to improve user QoE. We use Semi-Markov model to predict users' future cells and a novel …
Now a day's Heterogeneous wireless network is a promising field of research interest. Various challenges exist in this hybrid combination like load balancing, resource management and so on. In this paper we introduce a reliable load balancing architecture for heterogeneous wireless communications to ensure certain level of quality of service. To conquer the problem of centralized and distributed design, a semi distributed load balancing architecture for multiple access networks is introduced. In this grid based design multiple Load and Mobile Agent Management Units is incorporated. To prove th…
Explosive data traffic growth leads to a continuous surge in capacity demands across mobile networks. In order to provision high network capacity, small cell base stations (SCBSs) are widely deployed. Owing to the close proximity to mobile users, SCBSs can effectively enhance the network capacity and offloading traffic load from macro BSs (MBSs). However, the cost-effective backhaul may not be readily available for SCBSs, thus leading to backhaul constraints in small cell networks (SCNs). Enabling cache in BSs may mitigate the backhaul constraints in SCNs. Moreover, the dense deployment of SCB…
With technological advancements and constant changes of Internet, cloud computing has been today's trend. With the lower cost and convenience of cloud computing services, users have increasingly put their Web resources and information in the cloud environment. The availability and reliability of the client systems will become increasingly important. Today cloud applications slightest interruption, the impact will be significant for users. It is an important issue that how to ensure reliability and stability of the cloud sites. Load balancing would be one good solution. This paper presents a fr…
Efficient routing is one of the key challenges for next generation vehicular networks in order to provide fast and reliable communication in a smart city context. Various routing protocols have been proposed for determining optimal routing paths in highly dynamic topologies. However, it is the dilemma of those kinds of networks that good paths are used intensively, resulting in congestion and path quality degradation. In this paper, we adopt ideas from multipath routing and propose a simple decentral scheme for Mobile Ad-hoc Network (MANET) routing, which handles passive load balancing without…
Multihomed services can load-balance their incoming connection requests using DNS, resolving the name of the server with different addresses depending on the link load that corresponds to each address. Previous work has studied a number of problems with this approach, e.g., due to Time-to-Live duration violations and client proximity to local DNS servers. In this paper, we experimentally evaluate a DNS-based ingress traffic engineering system that we deployed at Georgia Tech. Our objective is to understand whether simple and robust load balancing algorithms can be accurate in practice, despite…
Network Functions Virtualization (NFV) aims to support service providers to deploy various services in a more agile and cost-effective way. However, the softwarization and cloudification of network functions can result in severe congestion and low network performance. In this paper, we propose a solution to address this issue. We analyze and solve the online load balancing problem using multipath routing in NFV to optimize network performance in response to the dynamic changes of user demands. In particular, we first formulate the optimization problem of load balancing as a mixed integer linea…
Using Machine Learning (ML) techniques for the next generation wireless networks have shown promising results in the recent years, due to high learning and adaptation capability of ML algorithms. More specifically, ML techniques have been used for load balancing in Self-Organizing Networks (SON). In the context of load balancing and ML, several studies propose network management automation (NMA) from the perspective of a single and centralized agent. However, a single agent domain does not consider the interaction among the agents. In this paper, we propose a more realistic load balancing appr…
Distributed multi-controller deployment is a promising method to achieve a scalable and reliable control plane of Software-Defined Networking (SDN). However, it brings a new challenge for balancing loads on the distributed controllers as the network traffic dynamically changes. The unbalanced load distribution on the controllers will increase response delay for processing flows and reduce the controllers'throughput. Switch migration is an effective approach to solve the problem. However, existing schemes focus only on the load balancing performance but ignore migration efficiency, which may re…
We propose in this paper a simulation implementation of self-organizing Networks optimization related to mobility load balancing (MLB) for lte systems using ns-3. the implementation is achieved toward two MLB algorithms dynamically adjusting handover (HO) parameters based on the reference signal received power measurements. such adjustments are done with respect to loads of both an overloaded cell and its cell neighbours having enough available resources enabling to achieve load balancing. numerical investigations through selected key performance indicators of the proposed MLB algorithms when …
Communication load balancing aims to balance the load between different available resources, and thus improve the quality of service for network systems. After formulating the load balancing (LB) as a Markov decision process problem, reinforcement learning (RL) has recently proven effective in addressing the LB problem. To leverage the benefits of classical RL for load balancing, however, we need an explicit reward definition. Engineering this reward function is challenging, because it involves the need for expert knowledge and there lacks a general consensus on the form of an optimal reward f…
In Cloud computing environment the resources are managed dynamically based on the need and demand for resources for a particular task. With a lot of challenges to be addressed our concern is Load balancing where load balancing is done for optimal usage of resources and reduces the cost associated with it as we use pay-as-you-go policy. The task scheduling is done by the cloud service provider using preemption and non-preemption based on the requirements in a virtualized scenario which has been focused here. In this paper, various task scheduling algorithms are studied to present the dynamic al…
In this paper, we analyze the performance of random load resampling and migration strategies in parallel server systems. Clients initially attach to an arbitrary server, but may switch server independently at random instants of time in an attempt to improve their service rate. This approach to load balancing contrasts with traditional approaches where clients make smart server selections upon arrival (e.g., Join-the-Shortest-Queue policy and variants thereof). Load resampling is particularly relevant in scenarios where clients cannot predict the load of a server before being actually attached …
Self-Organizing Network (SON) technology aims at autonomously deploying, optimizing and repairing the Radio Access Networks (RAN). SON algorithms typically use Key Performance Indicators (KPIs) from the RAN. It is shown that in certain cases, it is essential to take into account the impact of the backhaul state in the design of the SON algorithm. We revisit the Base Station (BS) load definition taking into account the backhaul state. We provide an analytical formula for the load along with a simple estimator for both elastic and guaranteed bit-rate (GBR) traffic. We incorporate the proposed lo…
The centralized architecture in software-defined network (SDN) provides a global view of the underlying network, paving the way for enormous research in the area of SDN traffic engineering (SDN TE). This research focuses on the load balancing aspects of SDN TE, given that the existing reactive methods for data-plane load balancing eventually result in packet loss and proactive schemes for data plane load balancing do not address congestion propagation. In the proposed work, the SDN controller periodically monitors flow level statistics and utilization on each link in the network and over-utili…
In this paper, we study the performance of multicarrier mobile networks. Specifically, we analyze the flow-level performance of two inter-carrier load balancing schemes and the gain engendered by Carrier Aggregation (CA). CA is one of the most important features of HSPA+ and LTE-A networks; it allows devices to be served simultaneously by several carriers. We propose two load balancing schemes, namely Join the Fastest Queue (JFQ) and Volume Balancing (VB), that allow the traffic of CA and non-CA users to be distributed over the aggregated carriers. We then evaluate the performance of these sch…
This paper studies the problem of load-balancing the demand for content in a peer-to-peer network across heterogeneous peer nodes that hold replicas of the content. Previous decentralized load balancing techniques in distributed systems base their decisions on periodic updates containing information about load or available capacity observed at the serving entities. We show that these techniques do not work well in the peer-to-peer context; either they do not address peer node heterogeneity, or they suffer from significant load oscillations. We propose a new decentralized algorithm, Max-Cap, ba…
This article proposes a design and implementation of a low cost two-tier architecture model for high availability cluster combined with load-balancing and shared storage technology to achieve desired scale of three-tier architecture for application load balancing e.g. web servers. The research work proposes a design that physically omits Network File System (NFS) server nodes and implements NFS server functionalities within the cluster nodes, through Red Hat Cluster Suite (RHCS) with High Availability (HA) proxy load balancing technologies. In order to achieve a low-cost implementation in term…
Edge computing servers like cloudlets from different service providers compensate scarce computational, memory, and energy resources of mobile devices, are distributed across access networks. However, depending on the mobility pattern and dynamically varying computational requirements of associated mobile devices, cloudlets at different parts of the network become either overloaded or under-loaded. Hence, load balancing among neighboring cloudlets appears to be an essential research problem. Nonetheless, the existing load balancing frameworks are unsuitable for low-latency applications. Thus, …
Most load balancing techniques implemented in current data centers tend to rely on a mapping from packets to server IP addresses through a hash value calculated from the flow five-tuple. The hash calculation allows extremely fast packet forwarding and provides flow `stickiness', meaning that all packets belonging to the same flow get dispatched to the same server. Unfortunately, such static hashing may not yield an optimal degree of load balancing, e.g., due to variations in server processing speeds or traffic patterns. On the other hand, dynamic schemes, such as the Join-the-Shortest-Queue (J…
Cloud computing has been gaining popularity in the recent years. Several studies are being proceeded to build cloud applications with exquisite quality based on users demands. In achieving the same, one of the applied criteria is checkpoint based load balancing in real time scheduling through which suitable cloud service is chosen from a group of cloud services candidates. Valuable information can be collected to rank the services within this checkpoint based load balancing. In order to attain ranking, different services are needed to be invoked in the cloud, which is time consuming and wastag…
Load-Balancers play an important role in data centers as they distribute network flows across application servers and guarantee per-connection consistency. It is hard however to make fair load balancing decisions so that all resources are efficiently occupied yet not overloaded. Tracking connection states allows to infer server load states and make informed decisions, but at the cost of additional memory space consumption. This makes it hard to implement on programmable hardware, which has constrained memory but offers line-rate performance. This paper presents Charon, a stateless load-aware l…
Data center networks offer multiple disjoint paths between Top-of-Rack (ToR) switches to connect server racks providing large bisection bandwidth. An effective load-balancing mechanism is required in order to fully utilize the available capacity of the multiple paths. While packet-based load-balancing can achieve high utilization, it suffers from reordering. Flow-based load-balancing such as equal-cost multipath routing (ECMP) spreads traffic uniformly across multiple paths leading to frequent hash collisions and suboptimal performance. Finally, flowlet based load-balancing such as CONGA or HU…
Nowadays, centralized Path Computation Elements (PCE) integrate control plane algorithms to optimize routing and load-balancing continuously. When a link fails, the traffic load is automatically transferred to the remaining paths according to the configuration of load-balancers. In this context, we propose a load-balancing method that anticipates load transfers to ensure the protection of traffic against any Shared Risk Link Group (SRLG) failure. The main objective of this approach is to make better use of bandwidth compared to existing methods. It consists in reserving a minimum amount of ext…
In P2P systems, large volumes of data are declustered naturally across a large number of peers. But it is very difficult to control the initial data distribution because every user has the freedom to share any data with other users. The system scalability can be improved by distributing the load across multiple servers which is proposed by replication. The large scale content distribution systems were improved broadly using the replication techniques. The demanded contents can be brought closer to the clients by multiplying the source of information geographically, which in turn reduce both th…
Current-day data centers and high-volume cloud services employ a broad set of heterogeneous servers. In such settings, client requests typically arrive at multiple entry points, and dispatching them to servers is an urgent distributed systems problem. This paper presents an efficient solution to the load balancing problem in such systems that improves on and overcomes problems of previous solutions. The load balancing problem is formulated as a stochastic optimization problem, and an efficient algorithmic solution is obtained based on a subtle mathematical analysis of the problem. Finally, ext…
This paper presents the network load balancing problem, a challenging real-world task for multi-agent reinforcement learning (MARL) methods. Traditional heuristic solutions like Weighted-Cost Multi-Path (WCMP) and Local Shortest Queue (LSQ) are less flexible to the changing workload distributions and arrival rates, with a poor balance among multiple load balancers. The cooperative network load balancing task is formulated as a Dec-POMDP problem, which naturally induces the MARL methods. To bridge the reality gap for applying learning-based methods, all methods are directly trained and evaluate…
Information-Centric Networking is still an incomplete paradigm which introduces a large variety of new topics and approaches over the traditional networking. Since it is a relatively new concept which promises for easier and faster data access many aspects of it have been studied intensely in recent years. Nonetheless, load balancing is one of the least focused but high potency, open-ended areas. The aim of this project is to present an alternative technique to load balancing in the domain of pre-suggested routing method LSCR (Link State Content Routing). We suggested multi-path interest and m…
This paper first presents a parallel solution for the Flowshop Scheduling Problem in parallel environment, and then proposes a novel load balancing strategy. The proposed Proportional Fairness Strategy (PFS) takes computational performance of computing process sets into account, and assigns additional load to computing nodes proportionally to their evaluated performance. In order to efficiently utilize the power of parallel resource, we also discuss the data structure used in communications among computational nodes and design an optimized data transfer strategy. This data transfer strategy co…
A flooding attack in wireless sensor networks is a type of threat that shortens the lifetimes of the sensor networks. Although flooding attack prevention techniques have been proposed, if a continuous flooding attack occurs, the sensor node energy is depleted during detection. In this paper, we use multi-path routing to solve this problem. In order to balance the load of the sensor node, energy balancing of the sensor node is controlled by determining the number of pathways using fuzzy logic. By adjusting the energy balancing of the sensor nodes, the number of energy-exhausting sensor nodes ca…
Small-cell architecture is widely adopted by cellular network operators to increase network capacity. By reducing the size of cells, operators can pack more (low-power) base stations in an area to better serve the growing demands, without causing extra interference. However, this approach suffers from low spectrum temporal efficiency. When a cell becomes smaller and covers fewer users, its total traffic fluctuates significantly due to insufficient traffic aggregation and exhibiting a large "peak-to-mean" ratio. As operators customarily provision spectrum for peak traffic, large traffic tempora…
In hierarchical Mobile IPv6 networks, Mobility Anchor Point (MAP) may become a single point of bottleneck as it handles more and more mobile nodes (MNs). A number of schemes have been proposed to achieve load balancing among different MAPs. However, signaling reduction is still imperfect because these schemes also avoid the effect of the number of CNs. Also only the balancing of MN is performed, but not the balancing of the actual traffic load, since CN of each MN may be different. This paper proposes an efficient admission control algorithm along with a replacement mechanism for HMIPv6 networ…
Geographical load balancing can optimize the utilization of green energy and the cost of electricity by taking the advantages of green and price diversities at geographical dispersed data centers. However, higher green energy utilization or lower electricity cost may actually increase the total energy consumption, and is not necessarily the best option. The achievable energy tradeoffs can be captured by taking into consideration of a defined service efficiency parameter for geo-dispersed data centers.
Components connected over a network influence each other and interact in various ways. Examples of such systems are networks of computing nodes, which the nodes interact by exchanging workload, for instance, for load balancing purposes. In this paper, we first study the Influence Model, a networked Markov chain framework, for modeling network interactions and discuss two key limitations of this model, which cause it to fall short in modeling constraint-based and dynamic interactions in networks. Next, we propose the Dynamic and Constraint-based Influence Model (DCIM) to alleviate the limitatio…
This paper presents a self-optimizing solution for Mobility Load Balancing (MLB). The MLB-SON is performed in two phases. In the first, a MLB controller is designed using Multi-Objective Particle Swarm Optimization (MO-PSO) which incorporates a priori expert knowledge to considerably reduce the search space and optimization time. The dynamicity of the optimization phase is addressed. In the second phase, the controller is pushed into the base stations to implement the MLB SON. The method is applied to dynamically adapt Handover Margin parameters of a large scale LTE network in order to balance…
Network Function Virtualization (NFV) is a new paradigm, enabling service innovation through virtualization of traditional network functions located flexibly in the network in form of Virtual Network Functions (VNFs). Since VNFs can only be placed onto servers located in networked data centers, which is the NFV's salient feature, the traffic directed to these data center areas has significant impact on network load balancing. Network load balancing can be even more critical for an ordered sequence of VNFs, also known as Service Function Chains (SFCs), a common cloud and network service approac…
The performances of multimedia applications built on wireless systems depend on bandwidth availability that might heavily affect the quality of service. The IEEE 802.11 standards do not provide performed mechanism for bandwidth management through data load distribution among different APs of the network. Then, an AP can be heavily overloaded causing throughput degradation. Load Balancing Algorithms (LBAs) was been considered as one of the attractive solution to share the traffic through the available access points bandwidths. However, applying the load balancing algorithm and shifting a mobile…
Load Balancing plays a vital role in modern data centers to distribute traffic among instances of network functions or services. State-of-the-art load balancers such as Silkroad dispatch traffic obliviously without considering the real-time utilization of service instances and therefore can lead to uneven load distribution and suboptimal performance. In this paper, we design and implement Spotlight, a scalable and distributed load balancing architecture that maintains connection-to-instance mapping consistency at the edge of data center networks. Spotlight uses a new stateful flow dispatcher w…
Random hashing is a standard method to balance loads among nodes in Peer-to-Peer networks. However, hashing destroys locality properties of object keys, the critical properties to many applications, more specifically, those that require range searching. To preserve a key order while keeping loads balanced, Ganesan, Bawa and Garcia-Molina proposed a load-balancing algorithm that supports both object insertion and deletion that guarantees a ratio of 4.237 between the maximum and minimum loads among nodes in the network using constant amortized costs. However, their algorithm is not straightforwa…
