• Journal of Internet Computing and Services
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• v.9 no.2
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• pp.139-145
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• 2008

CRM(Customer Relationship Management) improves the competitiveness of small companies to large enterprises. E-mail, SMS (Short Message Service), telephony service, DM (Direct Mail) are used for customer response in many companies. In order to improve company's profit, business diversification is in progress with protecting the succession of existing customers, and the only of new customers. Futhermore, BPR (Business Process Re-engineering) and BPM (Business Process Management) of the CRM can be easily found in many companies, because it is the first contact point to the company at the customer's view. This paper discusses the development of CRM, and proposes a call object routing agent that is the main engine of the CRM. Result of performance evaluation of proposed method show that the system is effective and powerful enough to use at the multi-channel environment.

• Journal of KIISE:Information Networking
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• v.33 no.4
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• pp.299-309
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• 2006

In Mobile ad hoc networks, AODV is one of the famous on-demand routing protocol, which use the routing tables in the nodes if possible, or Route Discovery Process (RDP) is triggered to find a new route. However increasing the traffic of RDP causes dropping of the network performance in the large size of ad hoc networks. In this paper, we propose a novel routing protocol, named as AOZDV (Ad hoc On-demand Zone and Distance-Vector Routing), which enhances the AODV protocol with zone routing. AOZDV creates a Zone with neighbor nodes of the source/destination using traffic and power information, and utilizes Destination-Vector Table for internal routing in the Zone. We show by simulations that AOZDV can reduce the occurrence rate of route fail and RDP caused by route fail compared to existing routing protocols such as DSR and AODV.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.8
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• pp.1820-1826
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• 2013

Heterogeneous field sensor network between sensor to sensor is designed the CAN method to bus type structure in most using at industry. This Network is supporting a distance vector routing protocol on a characteristic structural a bus type. Also This network support to convert as making separate routing table in heterogeneous network. However distance vector routing protocol make a problem of decrease efficiency because of restriction of network expandability and low transmission process. We propose new CAN routing protocol to support network expandability and high transmission process of industry network. New CAN routing protocol structure addition priority and optional function field based on RIPv2. We established heterogeneous field sensor network, we measure data Throughput(bits/sec) for confirm new CAN routing protocol to increase efficient in industry.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.137-144
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• 2022

Wireless community networks (WCNs) are considered another form of ownership of internet protocol (IP) networks, where community members manage and own every piece of equipment in a decentralized way, and routing for traffic is done in a cooperative manner. However, the current routing protocols for WCNs suffer from stability and scalability issues. In this paper, an enhanced routing protocol is proposed based on the optimized link state routing (OLSR) protocol to meet the standards of efficiency in terms of stability and scalability. The proposed routing protocol is enhanced through two phases: multicasting expansion and multipoint relay (MPR) selection based on an analytical hierarchical process (AHP). The experimental results demonstrate that the proposed routing protocol outperforms the OLSR protocol in terms of network control overhead and packet delivery ratio by 18% and 1% respectively.

• The KIPS Transactions:PartC
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• v.16C no.6
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• pp.731-736
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• 2009

In wireless sensor network, many sensor nodes are distributed in the field. They communicate the sensing data each other and forward it to sink. Routing protocols, which define the delivery methods of sending data, affect to the lifetime of sensor network. This paper proposes RTAF that is a routing-tree construction algorithm of sensor nodes by a single flooding process in wireless sensor network. A routing tree is constructed by selecting a parent node using the forward-direction flooding packet and gathering children nodes using the reverse-direction flooding packet. In this process, a node with much energy becomes the parent node. And the routing tree is periodically reconstructed in order to distribute the loads of parent nodes. The proposed algorithm compared performance with Modified-LEACH using NS2 network simulation tool. The simulation result shows that the proposed algorithm constructs a routing-tree faster and reduced 40-80% in routing-tree construction packet.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.2805-2826
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• 2021

In most cases, the routing policy of networks shows a preference for a static one-to-one mapping of communication pairs to routing paths, which offers adversaries a great advantage to conduct thorough reconnaissance and organize an effective attack in a stress-free manner. With the evolution of network intelligence, some flexible and adaptive routing policies have already proposed to intensify the network defender to turn the situation. Routing mutation is an effective strategy that can invalidate the unvarying nature of routing information that attackers have collected from exploiting the static configuration of the network. However, three constraints execute press on routing mutation deployment in practical: insufficient route mutation space, expensive control costs, and incompatibility. To enhance the availability of route mutation, we propose an OpenFlow-based route mutation technique called Polymorphic Path Transferring (PPT), which adopts a physical and virtual path segment mixed construction technique to enlarge the routing path space for elevating the security of communication. Based on the Markov Decision Process, with considering flows distribution in the network, the PPT adopts an evolution routing path scheduling algorithm with a segment path update strategy, which relieves the press on the overhead of control and incompatibility. Our analysis demonstrates that PPT can secure data delivery in the worst network environment while countering sophisticated attacks in an evasion-free manner (e.g., advanced persistent threat). Case study and experiment results show its effectiveness in proactively defending against targeted attacks and its advantage compared with previous route mutation methods.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.2
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• pp.107-114
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• 2024

Mobile ad hoc networks represent self-configuring networks of mobile devices that communicate without relying on a fixed infrastructure. However, traditional routing protocols in such networks encounter challenges in selecting efficient and reliable routes due to dynamic nature of these networks caused by unpredictable mobility of nodes. This often results in a failure to meet the low-delay and low-energy consumption requirements crucial for such networks. In order to overcome such challenges, our paper introduces a novel multi-objective and adaptive routing scheme based on the Q-learning reinforcement learning algorithm. The proposed routing scheme dynamically adjusts itself based on measured network states, such as traffic congestion and mobility. The proposed approach utilizes Q-learning to select routes in a decentralized manner, considering factors like energy consumption, load balancing, and the selection of stable links. We present a formulation of the multi-objective optimization problem and discuss adaptive adjustments of the Q-learning parameters to handle the dynamic nature of the network. To speed up the learning process, our scheme incorporates informative shaped rewards, providing additional guidance to the learning agents for better solutions. Implemented on the widely-used AODV routing protocol, our proposed approaches demonstrate better performance in terms of energy efficiency and improved message delivery delay, even in highly dynamic network environments, when compared to the traditional AODV. These findings show the potential of leveraging reinforcement learning for efficient routing in ad hoc networks, making the way for future advancements in the field of mobile ad hoc networking.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.1
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• pp.108-113
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• 2012

Routing paths are mightily important for the network security in WSNs. To maintain such routing paths, sustained path re-selection and path management are needed. Region segmentation based path selection method (RSPSM) provides a path selection method that a sensor network is divided into several subregions, so that the regional path selection and path management are available. Therefore, RSPSM can reduce energy consumption when the path re-selection process is executed. However, it is hard to guarantee optimized secure routing path at all times since the information using the path re-selection process is limited in scope. In this paper, we propose partial path selection method in each subregion using preselected partial paths made by RSPSM for routing path optimization in SEF based sensor networks. In the proposed method, the base station collects the information of the all partial paths from every subregion and then, evaluates all the candidates that can be the optimized routing path for each node using a evaluation function. After the evaluation process is done, the result is sent to each super DN using the global routing path information (GPI) message. Thus, each super DN provides the optimized secure routing paths using the GPI. We show the effectiveness of the proposed method via the simulation results. We expect that our method can be useful for the improvement of RSPSM.

• Journal of Communications and Networks
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• v.3 no.4
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• pp.374-382
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• 2001

Nowadays, the commonly used table lookup scheme for IP routing is based on the sc-called classless interdomain routing (CIDR). With CIDR, routers must find out the best matching prefix (BMP) for IP packets forwarding, this complicates the IP lookup. Currently, this process is mainly performed in software and several schemes hale been proposed for hardware implementation. Since the IP lookup performance is a major design issue for the new generation routers, in this article we investigate the properties of the routing table and present a new approach for IP lookups, our approach is not based Gn BMP and significantly reduces the complexity, thus the computation cast of existing schemes can be significantly reduced. We also propose an efficient IP lookup algorithm, with which we improve the binary search on prefixes to 30 millions of packets per second (MPPS) and 5,000 route updates/s under the same experiment setup with an even larger routing table.

• Journal of the Korea Society of Computer and Information
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• v.16 no.2
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• pp.93-99
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• 2011

In this paper, we propose a policy-gradient routing scheme under Reinforcement Learning that can be used adaptive QoS routing. A policy-gradient RL routing can provide fast learning of network environments as using optimal policy adapted average estimate rewards gradient values. This technique shows that fast of learning network environments results in high success rate of routing. For prove it, we simulate and compare with three different schemes.