• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.12
• /
• pp.5286-5306
• /
• 2016

Emerging applications in automation, medical imaging, traffic monitoring and surveillance need real-time data transmission over Wireless Sensor Networks (WSNs). Guaranteeing Quality of Service (QoS) for real-time traffic over WSNs creates new challenges. Rapid penetration of smart devices, standardization of Machine Type Communications (MTC) in next generation 5G wireless networks have added new dimensions in these challenges. In order to satisfy such precise QoS constraints, in this paper, we propose a new cross-layer QoS-provisioning strategy in Wireless Multimedia Sensor Networks (WMSNs). The network layer performs statistical estimation of sensory QoS parameters. Identifying QoS-routing problem with multiple objectives as NP-complete, it discovers near-optimal QoS-routes by using evolutionary genetic algorithms. Subsequently, the Medium Access Control (MAC) layer classifies the packets, automatically adapts the contention window, based on QoS requirements and transmits the data by using routing information obtained by the network layer. Performance analysis is carried out to get an estimate of the overall system. Through the simulation results, it is manifested that the proposed strategy is able to achieve better throughput and significant lower delay, at the expense of negligible energy consumption, in comparison to existing WMSN QoS protocols.

• Proceedings of the Korea Contents Association Conference
• /
• 2009.05a
• /
• pp.884-888
• /
• 2009

Vehicular Adhoc Networks (VANET), a Vehicle-to-Infrastucture or Vehicle-to-Vehicle communication technology, is an area that makes more specific use of Mobile Adhoc Networks(MANET). VANET's Quality of Service(QoS) focuses on preventing possible emergencies like car crash from happening by immediately transmitting information to the cars around, while MANET's QoS is being studied for the quality of multimedia data such as Video on Demand(VoD), Video streaming, Voice over IP(VoIP), etc. In this paper, I structure the actual network configuration using Link State Routing(LSR), implement QoS Provisioning Model using Common Open Policy Service(COPS), and suggest more effective k-hop Cluster and inter-domain policy negotiation which fit better to the characteristics of VANET.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.8 no.1
• /
• pp.92-101
• /
• 2009

In this paper, we propose a dynamic bandwidth provisioning method based on traffic forecasting in IEEE 802.16e packet core network. The traffic is categorized as 4-different classes and the traffic amount of each class is forecasted by the Box-Jenkins method. To increase the service provider's revenue we provision the bandwidth of 4-different classes dynamically using greedy algorithm. The simulation results show that the number of packet drops is reduced and the level of QoS is improved compared with two different the methods - no priority considering and static provisioning.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.31 no.1A
• /
• pp.30-37
• /
• 2006

In this paper, we propose a QoS-aware efficient bandwidth re-provisioning scheme in a next generation wireless packet transport network. At the transport network layer, it classifies the traffic of the radio network layer into a real time class and a non-real time class. Using an auto-regressive time-series model and a given packet loss probability, our scheme predicts the needed bandwidth of the non-real time class at every re-provisioning interval. Our scheme increases the system capacity by releasing the unutilized bandwidth of the non-real time traffic class for the real-time traffic class while insuring a controllable upper bound on the packet loss probability of a non-real time traffic class. Through empirical evaluations using the real Internet traffic traces, our scheme is validated that it can increase the bandwidth efficiency while guaranteeing the quality of service requirements of the non-real time traffic class.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.6 no.1
• /
• pp.178-202
• /
• 2012

In this paper, we first survey cross-layer architectures for Wireless Sensor Networks (WSNs) and Wireless Multimedia Sensor Networks (WMSNs). Afterwards, we propose a novel cross-layer architecture for QoS provisioning in clustered and multi-hop based WMSNs. The proposed architecture provides support for multiple network-based applications on a single sensor node. For supporting multiple applications on a single node, an area in memory is reserved where each application can store its network protocols settings. Furthermore, the proposed cross-layer architecture supports heterogeneous flows by classifying WMSN traffic into six traffic classes. The architecture incorporates a service differentiation module for QoS provisioning in WMSNs. The service differentiation module defines the forwarding behavior corresponding to each traffic class. The forwarding behavior is primarily determined by the priority of the traffic class, moreover the service differentiation module allocates bandwidth to each traffic class with goals to maximize network utilization and avoid starvation of low priority flows. The proposal incorporates the congestion detection and control algorithm. Upon detection of congestion, the congested node makes an estimate of the data rate that should be used by the node itself and its one-hop away upstream nodes. While estimating the data rate, the congested node considers the characteristics of different traffic classes along with their total bandwidth usage. The architecture uses a shared database to enable cross-layer interactions. Application's network protocol settings and the interaction with the shared database is done through a cross-layer optimization middleware.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.3
• /
• pp.1164-1183
• /
• 2019

The rapid development of cloud computing and high requirements of operators requires strong support from the underlying Data Center Networks. Therefore, the effectiveness of using resources in the data center networks becomes a point of concern for operators and material for research. In this paper, we discuss the online virtual-cluster provision problem for multiple tenants with an aim to decide when and where the virtual cluster should be placed in a data center network. Our objective is maximizing the total revenue for the data center networks under the constraints. In order to solve this problem, this paper divides it into two parts: online multi-tenancy scheduling and virtual cluster placement. The first part aims to determine the scheduling orders for the multiple tenants, and the second part aims to determine the locations of virtual machines. We first approach the problem by using the variational inequality model and discuss the existence of the optimal solution. After that, we prove that provisioning virtual clusters for a multi-tenant data center network that maximizes revenue is NP-hard. Due to the complexity of this problem, an efficient heuristic algorithm OMS (Online Multi-tenancy Scheduling) is proposed to solve the online multi-tenancy scheduling problem. We further explore the virtual cluster placement problem based on the OMS and propose a novel algorithm during the virtual machine placement. We evaluate our algorithms through a series of simulations, and the simulations results demonstrate that OMS can significantly increase the efficiency and total revenue for the data centers.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.11
• /
• pp.3584-3602
• /
• 2022

NFV realizes flexible and rapid software deployment and management of network functions in the cloud network, and provides network services in the form of chained virtual network functions (VNFs). However, using VNFs to provide quality guaranteed services is still a challenge because of the inherent difficulty in intelligently scaling VNFs to handle traffic fluctuations. Most existing works scale VNFs with fixed-capacity instances, that is they take instances of the same size and determine a suitable deployment location without considering the cloud network resource distribution. This paper proposes a traffic forecasted assisted proactive VNF scaling approach, and it adopts the instance capacity adaptive to the node resource. We first model the VNF scaling as integer quadratic programming and then propose a proactive adaptive VNF scaling (PAVS) approach. The approach employs an efficient traffic forecasting method based on LSTM to predict the upcoming traffic demands. With the obtained traffic demands, we design a resource-aware new VNF instance deployment algorithm to scale out under-provisioning VNFs and a redundant VNF instance management mechanism to scale in over-provisioning VNFs. Trace-driven simulation demonstrates that our proposed approach can respond to traffic fluctuation in advance and reduce the total cost significantly.

• International Journal of Computer Science & Network Security
• /
• v.22 no.3
• /
• pp.95-100
• /
• 2022

Cloud computing platform is a shared pool of resources and services with various kind of models delivered to the customers through the Internet. The methods include an on-demand dynamically-scalable form charged using a pay-per-use model. The main problem with this model is the allocation of resource in dynamic. In this paper, we have proposed a mechanism to optimize the resource provisioning task by reducing the job completion time while, minimizing the associated cost. We present the Cooperative Agents Dynamic Resource Allocation and Monitoring in Cloud Computing CADRAM system, which includes more than one agent in order to manage and observe resource provided by the service provider while considering the Clients' quality of service (QoS) requirements as defined in the service-level agreement (SLA). Moreover, CADRAM contains a new Virtual Machine (VM) selection algorithm called the Node Failure Discovery (NFD) algorithm. The performance of the CADRAM system is evaluated using the CloudSim tool. The results illustrated that CADRAM system increases resource utilization and decreases power consumption while avoiding SLA violations.

• Journal of KIISE:Computer Systems and Theory
• /
• v.26 no.8
• /
• pp.984-998
• /
• 1999

최근 개인 휴대 통신에 대한 관심도가 증가하면서 B-ISDN (Broadband Integrated Services Digital Network)과 같은 기존의 유선 망에서 제공하던 다양한 멀티미디어 응용 지원을 무선 망으로 확장시키기 위한 연구가 활발히 진행되고 있다. 그러나 기존의 유선 망에서는 멀티미디어 응용 지원을 위해 QoS (Quality of Service) Provisioning에 관한 많은 연구가 되어 있으나 무선 망에서는 이동성과 무선 전파의 열악한 전송으로 인해 새로운 QoS Provisioning 방법에 관한 연구가 필수적이다. 본 논문에서는 이러한 무선 망의 특수성으로 인해 발생할 수 있는 서비스의 질 저하와 강제 종료를 줄임으로써 지속적인 QoS를 보장해 주고 한정된 무선 자원을 효율적으로 사용하며 처리에 의한 오버헤드를 줄이기 위하여 다음과 같은 세 가지 방법을 제안하였다. 첫째, 핸드오프 강제 종료율을 줄이기 위하여 대역폭 예약 방법을 사용하되 특정 셀의 트래픽 특성에 맞게 또한 시간대에 따른 트래픽 특성에 따라 예약 대역폭의 양을 조절하는 적응적 대역폭 예약 방법이다. 둘째, 많은 경우 각 셀의 트랙픽 변화는 일정한 주기로 변화한다는 특성에 따라 과거의 트래픽 정보를 이용하는 예측 기반의 대역폭 예약 방법이다. 마지막으로 호의 종류, 트래픽 특성, 단말기의 이동 속도에 따라 다른 우선 순위에 의해 호 수락 제어를 수행하는 우선 순위 기반의 호 수락 제어를 제안하였다. 시뮬레이션을 통하여 기존에 제안된 방법과 성능 비교하여, 요구되는 수준의 QoS 보장과 효율적인 자원의 사용, 요구되는 처리비용의 최소화를 통해 전체 시스템의 성능 향상을 입증하였다.Abstract As interest in wireless hand-held terminals and in personal communications services increases recently, there have been broad studies on the ways to support multimedia applications provided in wired networks such as B-ISDN (Broadband Integrated Services Digital Network) in wireless networks. However, since many studies have focused on Quality of Service (QoS) Provisioning in wired networks to provide multimedia applications, new methods of QoS Provisioning are needed in wireless networks to resolve the problem of wireless channel fading and the difficulty of mobility occurred in wireless networks. This paper proposes three schemes of QoS Provisioning in wireless networks which will make continuous QoS guarantee and efficient use of limited wireless resources possible. The first scheme reserves bandwidth in proportion to the amount of real-time traffic in the neighbor cells to decrease the handoff dropping rate of delay sensitive real-time connections, adapting reserved bandwidth for efficient resource utilization. The second scheme is predictive bandwidth reservation scheme that utilizes the past handoff information. It can decrease overheads required to adapt bandwidth reservation. The last scheme is priority-based call admission control prioritizing traffic type (real-time traffic/ non-real-time traffic), connection type (new connection /handoff connection), and mobile terminal speed (fast mobile/slow mobile). Simulation results show that the proposed QoS Provisioning schemes improve the total system performance by achieving three goals - required QoS guarantee, higher bandwidth utilization and less overhead.

• The Transactions of the Korea Information Processing Society
• /
• v.7 no.11S
• /
• pp.3633-3650
• /
• 2000

Internet is no longer a network for special communities but became a global means of communication infrastructure for everyday life. People are exchanging their personal messages using e-mails, students are getting their educational aids through the web, people are buying a variety of goods from cyber shopping malls, and companies are conducting their businesses over the Internet. Recently, such an explosive growth of the traffic in the Internet raised a big concern on how to accommodate ever-changing user's needs in terms of an amount of the traffic, characteristics of the traffic, and various service quality requirements, Over provisioning can be a simple solution but it is too expensive and inefficient. Thus many new technologies to solve this very difficult puzzle have bcen introduced recently, Any single solution, however, can be insufficient and a carefully designed architecture, which integrates a group of solutions, is required. In this paper, we propose a policy-based Internet QoS provisioning, traffic engineering and perfonnance management system as our solution to this problem. Our integrated management QoS solution can provide highly responsive flow-through service provisioning, more realistic service and resource policy control based on the real network performance information, and centralized control of traffic engineering for heterogeneous networks.