International Journal of Interactive Mobile Technologies (iJIM) – eISSN: 1865-7923 – Vol. 15, No. 03, 2021 Paper—A High-Performance Routing Protocol Based on Mobile Agent for Mobile Ad hoc Networks A High-Performance Routing Protocol Based on Mobile Agent for Mobile Ad Hoc Networks https://doi.org/10.3991/ijim.v15i03.13007 Quy Vu Khanh (), Pham Minh Chuan, Vi Hoai Nam, Dao Manh Linh Hung Yen University of Technology and Education, Hung Yen, Vietnam quyvk@utehy.edu.vn Nguyen Tien Ban Posts and Telecommunications Institute of Technology, Ha-Noi, Vietnam Nguyen Dinh Han Hanoi University of Science and Technology, Ha-Noi, Vietnam Abstract—In recent years, Mobile Ad Hoc Networks (MANETs) have been focused on research and applied in many domains such as healthcare, traffics, military, entertainment, and smart cities. However, the performance of MANETs is rather quite. Due to the mobile characteristic of network nodes, the routing is the main issue to improve network performance. In this study, we propose a rout- ing protocol, called IWCETT (Improve Weighted Cumulative Expected Trans- mission Time) protocol. This protocol is a modification of a well-known routing protocol, is Ad hoc On-demand Distance Vector, as a solution to improve the performance of MANETs. We adapted the mobile agent technology and a novel metric for routing in these networks. The metric is a function of the loss rate, the bandwidth and the end-to-end delay of the link. Indeed, we established a new tunable parameter to obtain a tradeoff between throughput and delay when com- puting the new metric. As a result, any routing protocol using this metric can always choose a high throughput and low delay path between a source and a des- tination. Hence, the achievable performance of the MANETs has been improved remarkably with our modified routing protocol. Keywords—High-Performance, Routing Protocol, IWCETT, MANETs 1 Introduction According to the Cisco Internet Report, it is expected that, by 2023, there will be over 29.3 billion networked global devices and the number of global mobile devices will grow over 13 billion. Over 70% of the global population will have mobile connec- tivity. Each capita will have an average of 3.6 networked devices. Business users expect high-performance connectivity anywhere, anytime, on any devices [1]. The Next Generation Networks (NGN) such as the 5th, 6th generation networks are being shaped and expected to become the leading communication technology of the 30 http://www.i-jim.org https://doi.org/10.3991/ijim.v15i03.13007 mailto:quyvk@utehy.edu.vn Paper—A High-Performance Routing Protocol Based on Mobile Agent for Mobile Ad hoc Networks Internet in the future. With NGN, the architecture and components of the mobile net- work will undergo a radical change. Here, the network architecture considers the device as the centre will replace the network architecture based on base stations in order to improve packet distribution. Mobile devices also are improved to adapt to the new role - being a central component of the network and must to be smarter to support effective communication technologies such as massive MIMO, Device-to-Device. Moreover, mobile devices will also be equipped with M2M modules, which capable of setting up M2M connections, is the principle of forming MANETs [2-3]. MANETs was born since the 1970s, have always been considered a very convenient communication tool. Despite being limited in ability and capacity, MANETs have proven to be outstanding advantages in communicating with flexible infrastructure. They are applied in very many domains such as smart cities [7], healthcare [8] smart traffic [9], military [10], emergency and disaster recovery [11-12], as well as promising a vital contribution to the future development of the Internet [13]. However, when the scale expands, MANETs face problems such as quite low per- formance, quality of service guarantees, energy efficiency. In MANETs, since mobility characteristics of the network nodes leading to network topology are changed continu- ously. Besides, network nodes must also cooperate to transmit data packets. Routing protocols are particularly important in improving network performance. Moreover, the performance of MANETs is generally quite low and depends on its size, communica- tion model and radio communication environment [2, 5-6, 14]. Therefore, designing high-performance routing protocols for MANETs is a significant challenge and is an urgent research direction. Survey researches in [2, 4-6] also show that the throughput and end-to-end delay are typical criteria reflecting network performance. In this study, we set up a new routing protocol, called IWCETT (Improve Weighted Cumulative Expected Transmission Time), based on extending known routing proto- cols for MANETs. Our main idea is to rely on mobile agents to obtain reliable routing information. First of all, we analyze the existing routing protocols to determine which routing protocols best suit the characteristics of MANETs. Then we expand to improve MANETs performance. 2 Routing Issues in MANETs In MANETs, two typical routing protocols standardized by IETF (The Internet En- gineering Task Force) are AODV (Ad hoc On-demand Distance Vector) [15] and DSR (Dynamic Source Routing) [16]. These are on-demand routing protocols that work on the principle that whenever a data is needed to transfer, the source node will discover and find a route to the destination node. The route discovery process starts with the source node sending broadcast the RREQ (Route Request) packets. Then, these packets are forwarded through intermediate nodes to reach the destination node (Fig. 2, the red line). The destination node or intermediate node (the node knows the route to the destination) will respond by sending unicast RREP (Route Reply) packet back to the source node (Fig. 2, the green line). Beside the route discovery procedure, IWCETT also has route maintenance procedures that use iJIM ‒ Vol. 15, No. 03, 2021 31 Paper—A High-Performance Routing Protocol Based on Mobile Agent for Mobile Ad hoc Networks RERR (Route Error) packets (Fig. 2, the yellow line). In this way, the source node receives all candidate routes. Although both are designed to fit with the characteristics of MANETs, there are still differences between AODV and DSR protocols. AODV does not establish a route in advance to transmit data from source to destination. The route will be determined by each network node when data arrives, based on the system status information obtained by the node. In addition, AODV uses the sequence numbers to determine the latest route and avoid loop routing. Meanwhile, DSR determines the route at the source node. The source node will identify all hops from the source node to the destination node. Therefore, the header of RREQ and RREP packets must be ex- panded to store the address information of intermediate nodes. Besides, unlike AODV, DSR maintains a temporary memory to save routes and use them until they are no longer valid. Fig. 1. The route discovery process in the AODV protocol Both AODV and DSR protocols use less resource, save energy and support the ar- chitecture/organization features of mobile ad hoc networks such as self-organizing, self-configuring and mobile. In some performance comparisons [17-19], AODV has the packet delivery ratio over 90%, while DSR performance is best in the networks with small hop numbers. However, using AODV for MANETs in NGN will have more ad- vantages than DSR. The main reason is the large scale and high mobility nature of MANETs in NGN. Meanwhile, the route discovery process of DSR can lead to the unpredictable length of control packets and data packets. 3 Mobile Agents In computer science, a mobile agent is an entity (software/data/packet) capable of operating in the environment, interacting with other agents or performing a specific V1 S V2 V3 V4 V6 V5 V8 Mobile node RREQ (Flooding) packet V7 D V9 X RREP packet RERR packet 32 http://www.i-jim.org Paper—A High-Performance Routing Protocol Based on Mobile Agent for Mobile Ad hoc Networks goal. A mobile agent used in the MANETs environment is small packets (probing pack- ets) that are sent periodically between neighbouring nodes to collect information. In recent time, the solutions use mobile agents to control routing protocols more and more popular, indicated in several studies [20-23]: Fig. 2. The proposed mobile agent structure: a) 𝐼 − 𝑅𝑒𝑞𝑢𝑒𝑠𝑡; b) 𝐼 − 𝑅𝑒𝑝𝑙𝑦. According to [21], the authors proposed an intelligent route planning based on mo- bile agents for ad hoc networks in IoT systems to make the best decision for selecting the next node in different moments. This study used the Markov Decision Process (MDP) as the underlying optimization model, which is well-known for its effectiveness to optimize decision making under uncertainty. In the proposed model, authors consid- ered the distance between the nodes, the distance between a node and the sink node, residual energy of the node and the priority of them as the MDP parameters. The expe- rience results show that the proposed solution improves the energy consumption of IoT nodes and the lifetime of the system, as well as maximizes the reliability of the network and reduce data transmission delay. Also, in this direction, in [22], the authors proposed a load balancing technique using mobile agents for MANETs aims to utilize maximum resources of the neighbour nodes and protect mobile agents from the malicious host using a hash function. Besides, this study also considers the impact of frequent network disconnection on agent movement. The simulation result shows that the proposed scheme improves robust against modifi- cation attacks on mobile agents. In [23], to improve the intelligence of the mobile agent for ad hoc networks, authors proposed a conceptual, theoretical framework named 𝑖𝐴𝑔𝑒𝑛𝑡, where 𝑖 means intelli- gent, and the agent refers to the mobile agent. This study shows details of four designs of 𝑖𝐴𝑔𝑒𝑛𝑡. Compared with the old mobile agent, the 𝑖𝐴𝑔𝑒𝑛𝑡 has a learning ability, which means that it can dynamically plan the path according to the network environ- ment in order to reduce energy consumption. Based on 𝑖𝐴𝑔𝑒𝑛𝑡, authors also proposed a method to determine the number of the 𝑖𝐴𝑔𝑒𝑛𝑡𝑠 and their visiting areas in the ad hoc network environment. The simulation results show that 𝑚𝑢𝑙𝑡𝑖 − 𝑖𝐴𝑔𝑒𝑛𝑡 algorithm sig- nificantly improves the network performance, saving energy and load balancing. Fig. 2 shows our mobile agent structure. In particular, the 𝑇𝑖𝑚𝑒𝑠𝑡𝑎𝑚𝑝 field is used to determine the period a probe packet needs to be transmitted between two neighbour- ing nodes. The meaning of the remaining fields is similar to what was described in [20]. There are two types of agents, respectively named I-Request and I-Reply, which corre- spond to two tasks: requesting information and responding to information. We set up every 20 (ms), a network node sends I-Request probe packets to neighbouring nodes. Upon receiving the I-Request packet, neighbouring nodes are responsible for sending Type Reserved Hop Count Dest_ID Dst_Seqno Src_ID Type Reserved Hop Count Timestamp Dest_ID Dst_Seqno Src_ID (a) (b) iJIM ‒ Vol. 15, No. 03, 2021 33 Paper—A High-Performance Routing Protocol Based on Mobile Agent for Mobile Ad hoc Networks back the I-Reply packet to provide information for the requesting node. Based on the information gathered, each node will decide to choose the most appropriate route. 4 Proposed Protocol The routing metric used in MANETs must reflect the quality, the stability of the connections and, the hop numbers. In this section, we propose a routing protocol that uses the Weighted Cumulative Expected Transmission Time (WCETT) metric to find the route with high throughput. First of all, the protocol proceeds to assign a weight to each hop based on the quality of each connection; these weights then combined to select the most appropriate route. The detail of our proposed protocol will be provided in the following subsections. 4.1 Route selection algorithm According to IETF, the route cost of AODV protocol is calculated by the total hop numbers that a packet must across from source to destination. However, choosing a route only based on this cost is not optimal. In order to improve the performance of MANETs, Couto et al. [24] proposed a new routing parameter to calculate the cost of the route, which is Expected Transmission Count (ETX). To determine the ETX value, each node sends probing packets to neighbouring nodes. Then, based on the probe packet numbers and the acknowledge packet number received, each node identified the successful transmission probability. Symbol 𝑑𝑓 and 𝑑𝑟 , respectively, are the probability of sending and receiving a packet successfully. The probability of an expected success- ful transmission/reception event on a hop is 𝑑𝑓 × 𝑑𝑟 . The ETX on link 𝐿 (a connection between two adjacent nodes) is determined by the following formula: 𝐸𝑇𝑋(𝐿) = 1 𝑑𝑓 × 𝑑𝑟 (1) ETX of the route 𝑃, is the sum of the 𝐸𝑇𝑋𝑠 on each hop 𝐿, with 𝐿 ∈ 𝑃. 𝐸𝑇𝑋(𝑃) = ∑ 𝐸𝑇𝑋(𝐿)𝐿∈𝑃 (2) With this method, the protocol will choose the route based on the packet delivery ratio. The simulation results in [24] show that MANETs performance is significantly improved when using the ETX metric instead of using hop numbers. However, the ETX metric is limited when only considering the packet delivery ratio without considering the data transmission speed. To solve this issue, Expected Transmission Time (ETT) metric was proposed in [25]. ETT is determined by integrating the throughput of the link and the ETX value. In other words, the ETT metric is determined by multiplying the ETT value by the bandwidth to obtain the period time needed for transmitting a packet on a hop. The symbol 𝑆 is the size of the packet and 𝐵 is the bandwidth on the link. The ETT value of link L is determined, as follows: 𝐸𝑇𝑇(𝐿) = 𝐸𝑇𝑋(𝐿) × 𝑆 𝐵 (3) 34 http://www.i-jim.org Paper—A High-Performance Routing Protocol Based on Mobile Agent for Mobile Ad hoc Networks By putting the bandwidth into calculating the path cost, ETT metric not only binds physical interventions but also influenced by the quality of each link. When using the ETT metric, the cost of the route is the total cost of links. However, the real cost is different from the expected cost because this solution not take the co- channel interference into account when the nodes use the same channel. Therefore, au- thors in [25] proposed the WCETT metric with the particular purpose of reducing co- channel interference. The solution is to try to minimize the number of nodes using the same channel throughout the route. This technique uses an average weight 𝛽 to balance between the total cost of the route with the effects of the bottleneck channel. In detail, [25] does not provide a way of determining the value of 𝛽, but based on the experi- mental results, this research determines that 𝛽 = 0.5 is appropriate. Consider the route with P hops, the total transmission time uses same channel j (as- suming the system has a maximum of k channels) determined as follows: 𝑋𝑗 = ∑ ETT(𝑖),𝐿𝑖𝑛𝑘 𝑖 on 𝑗 𝑐ℎ𝑎𝑛𝑛𝑒𝑙 1 ≤ 𝑗 ≤ 𝑘 (4) Due to the bottleneck channel will dominate route throughput (channel 𝑗 has the highest 𝑋𝑗 value). We proposal use an average weight 𝛽 between the highest 𝑋𝑗 value and the total ETTs on the route. Setting IWCETT is the improved cost function; we have obtained the formula: { 𝛽 = ∑ ETT(𝑖) 𝐷 𝑖=1 𝑋𝑗1≤𝑗≤𝑘 𝑚𝑎𝑥 IWCETT = ( 𝛽 1+𝛽 ) ∑ ETT(𝑖) 𝐷 𝑖=1 + ( 1 1+𝛽 ) 𝑋𝑗1≤𝑗≤𝑘 𝑚𝑎𝑥 (5) There are two ways to explain how to determine the 𝛽 parameter. Firstly, we can view it as the affection on the end-to-end throughput between the bottleneck channel and other channels in the route. Secondly, it is a representation of the relationship be- tween the hop, which has the most effect on throughput and the overall route. The av- erage weight can be considered as an attempt to balance these two issues. On the other hand, the total transmission time on the entire 𝑃 route (∑ ETT(𝑖)𝑃𝑖=1 ) is usually much higher than the transmission time on the channel with a bottleneck connection ( 𝑋𝑗1≤𝑗≤𝑘 𝑚𝑎𝑥 ). Therefore, in order to ensure the balance of influence between these two factors, we determine the binding coefficient 𝛽 as Eq. (5). The route selection algorithm of IWCETT is summarized as follows: iJIM ‒ Vol. 15, No. 03, 2021 35 Paper—A High-Performance Routing Protocol Based on Mobile Agent for Mobile Ad hoc Networks Algorithm 1: IWCETT Route Selection Algorithm 1 P=routeset(S,D) 2 Cost=∞, Selectedroute={∅} 3 For each p in P 4 X[k]={∅}, Total=0 5 For j=1 to sizeof(route[p]) 6 Total=Total+ETT[j] 7 If link[j].chanel=k then X[k]=X[k]+ETT[j] 8 Endfor 9 β=Total/max(X[k]) 10 Calculator(A-WCETT[i]) // Equation (5) 11 Endfor 12 Cost=∞ 13 For each p in P 14 If Cost< A-WCETT[p] then 15 Cost=A-WCETT[p]; Selectedroute=rouset[p] 16 Return(Selectedroute, Cost) An example of calculating IWCETT with different β values as in Fig. 3. Fig. 3. Illustrate candidate routes after the discovery procedure S S S S 2. 1. 3. 4. ETT = 8 ETT = 5 ETT = 9 ETT = 5 ETT = 8 ETT = 10 D ETT = 8 ETT = 8 ETT = 5 ETT = 9 D ETT = 10 ETT = 6 ETT = 10 ETT = 8 D ETT = 10 Channel 1 Channel 2 D ETT = 8 S ETT = 9 ETT = 5 ETT = 10 D ETT = 5 5. 36 http://www.i-jim.org Paper—A High-Performance Routing Protocol Based on Mobile Agent for Mobile Ad hoc Networks Table 1. Effect of β parameter to the cost function 𝑹𝒐𝒖𝒕𝒆 𝑻𝒐𝒕𝒂𝒍 (𝑬𝑻𝑻) Max (𝑿𝒋) 𝑾𝑪𝑬𝑻𝑻 𝜷 𝒑𝒓𝒐𝒑𝒐𝒔𝒆𝒅 𝑰𝑾𝑪𝑬𝑻𝑻 𝜷 = 𝟎. 𝟏 𝜷 = 𝟎. 𝟓 𝜷 = 𝟎. 𝟗 1 30 17 28.7 23.5 18.3 1.76 25.30 2 31 16 29.5 23.5 17.5 1.94 25.89 3 32 17 30.5 24.5 18.5 1.88 26.79 4 34 20 32.6 27 21.4 1.7 28.81 5 29 19 28 24 20 1.52 25.05 The calculation results in Table 1 show the instability in the route selection decision of WCETT and IWCETT protocols. For different values of 𝛽, WCETT selects different routes, specifically as follows: β=0.1, route 5 is selected, WCETTmin=28. β=0.5, route 1 or 2 is selected, WCETTmin=23.5. β=0.9, route 2 is selected, WCETTmin=17.5. Meanwhile, IWCETT with β parameter determined by the proposed method always selects a suitable and stable route (route 5) with IWCETTmin=25.05. 5 Experimental Result and Analysis In this section, we set up a simulation on NS2 software to evaluate the performance of MANETs according to the criteria: average delay, average throughput. The routing protocols are evaluated as AODV, WCETT and IWCETT, respectively. The simulation parameters are summarized in Table 2. Table 2. Simulation Parameter Parameter Value Simulation Area 1000x1000m Number Nodes 100 Throughput 11 Mbit/s Mobile Speed 3m/s Mobility Model Random Waypoint Traffic Type CBR/UDP Packet Size 512 Byte Wireless MAC Interface 802.11 Simulation Time 300s iJIM ‒ Vol. 15, No. 03, 2021 37 Paper—A High-Performance Routing Protocol Based on Mobile Agent for Mobile Ad hoc Networks Fig. 4. Performance evaluation based on criteria: End-to-End Delay In the first simulation, Fig. 4, we evaluated the performance of three protocols based on the criteria of average delay. The results show that the WCETT and IWCETT pro- tocols have lower latency than the AODV protocol. These simulation results are fit with the theoretical calculations. Since WCETT and IWCETT operate multichannel, they have a higher data transfer rate and reduce congestion in the system. However, when the number of end-to-end connections increases to 20, the average delay of all three protocols tends to increase. However, the delay of AODV is still higher than the other two protocols. Fig. 5. Performance evaluation based on criteria: Average Throughput 38 http://www.i-jim.org Paper—A High-Performance Routing Protocol Based on Mobile Agent for Mobile Ad hoc Networks The second simulation, Fig. 5, we evaluate the performance of three protocols based on the criterion of average throughput. The simulation results show that the throughput of IWCETT is always higher than the other two protocols. Specifically, IWCETT and WCETT have the throughput that is nearly three times higher than the AODV protocol. However, as the number of end-to-end connections increases, the system throughput of all three protocols decreases. Notably, when the number of end-to-end connections in- creases to 25, the throughput is declined suddenly due to the happening environmental conflicts and system collision. In case the number of end-to-end connections is too large, the MANETs have tends to be congested on a large scale, and the performance of IWCETT will not improve over WCETT. Based on detailed simulation results, it shows that the IWCETT and WCETT proto- cols operate multiple channels, thus increasing throughput and reducing congestion on the overall system. The proposed protocol improves delay and throughput better than WCETT protocol due to optimized 𝛽 parameter. Besides, thanks to the use of multi- channel technology, two protocols achieved low delay and improved throughput many times more than the AODV protocol. One of the significant concerns for the effective- ness of the IWCETT protocol is the system cost relating to the use of mobile agents. In the next time, we will focus on study this issue. 6 Conclusion In this work, we proposed an on-demand routing protocol for MANETs, called IWCETT. This protocol is an improvement from AODV, multichannel operation and based on mobile agents. Simulation results show that IWCETT with improvements in 𝛽 parameters and mobile agent-based routing increased performance better than WCETT protocol. The simulation results also proved that the IWCETT and WCETT protocols have much higher throughput and lower delay than the AODV protocol. How- ever, in this works, authors still not yet consider the issue of information security when using mobile agent solution. 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J. De Couto, Daniel Aguayo, John Bicket, Robert Morris, A High Throughput Path Metric for Multi-Hop Wireless Routing. Wireless Networks, 2005. 11: p. 419–434. https://doi.org/10.1007/s11276-005-1766-z [25] R. Draves, J. Padhye, B. Zill, Routing in Multi-Radio, Multi-Hop Wireless Mesh Networks. Proceedings of the 10th Annual International Conference on Mobile Computing and Net- working (MobiCom). 2004. ACM. https://doi.org/10.1145/1023720.1023732 9 Authors Vu Khanh Quy was born in Hai Duong Province, Vietnam, in 1982. He received his B.Sc. degree from Hung Yen University of Technology and Education (UTEHY) in 2007 and his M.Sc. degree from Posts and Telecommunications Institute of Tech- nology (PTIT), in 2012. Currently, he is a PhD student at Faculty of Telecommunica- tions 1, PTIT and a lecturer at Faculty of Information Technology, UTEHY. His re- search interests include Wireless Communications, Mobile Ad Hoc Computing and Next-Generation Networks. (Email: quyvk@utehy.edu.vn). Pham Minh Chuan was born in Thai Binh Province, in 1980. He had a bachelor degree in Applied Mathematics and Informatics from Hanoi University of Science and Technology in 2003. He received a Master of Science in Applied Mathematics and In- formatics from this same University in 2008. He received his doctorate in information systems major in 2018 at Hanoi University of Science and Technology. He is a lecturer at Faculty of Information Technology, UTEHY. (Email: chuanpm@utehy.edu.vn). Vi Hoai Nam was born in Phu Tho Province, Viet Nam, in 1986. He received his B.Sc. degree from the Posts and Telecommunications Institute of Technology, in 2009 and received his M.S. degree from Ha Noi University of Technology, in 2013. Cur- rently, he is a lecturer at UTEHY. His research interests include Wireless Sensor Net- works, Next-Generation Networks. vihoainam@utehy.edu.vn Dao Manh Linh was born in Hung Yen Province, Vietnam, in 1988. He received his B.Sc. degree from UTEHY in 2013 and his M.Sc. degree from Posts and Telecom- munications Institute of Technology (PTIT), in 2016. Currently, he is a researcher at UTEHY. His research interests include Wireless Communications, Mobile Ad-hoc Net- work and Next-Generation Networks. daomanhlinh@utehy.edu.vn iJIM ‒ Vol. 15, No. 03, 2021 41 https://doi.org/10.32913/rd-ict.vol1.no37.260 https://doi.org/10.1109/sege.2018.8499517 https://doi.org/10.1109/optronix.2019.8862375 https://doi.org/10.1109/access.2019.2926286 https://doi.org/10.1007/s11276-005-1766-z https://doi.org/10.1145/1023720.1023732 mailto:quyvk@utehy.edu.vn mailto:chuanpm@utehy.edu.vn vihoainam@utehy.edu.vn daomanhlinh@utehy.edu.vn Paper—A High-Performance Routing Protocol Based on Mobile Agent for Mobile Ad hoc Networks Nguyen Tien Ban was born in Vinh Phuc Province, Viet Nam, in 1967. He gradu- ated from Leningrad University of Electrical Engineering (LETI), received his doctor- ate at Saint-Petersburg State University of Telecommunications (SUT), Russian Feder- ation in 2003. Currently, he is an associate professor in Telecommunication Faculty 1, Posts and Telecommunications Institute of Technology. His research areas are: Net- work Performance Analysis and Design, Network Design and Optimization, Modeling and Simulation of Telecommunication Systems. ban.ptit@gmail.com Nguyen Dinh Han was born in Hung-Yen, Vietnam, in 1977. Graduated from Hanoi National University in 2000, graduate from AIT in 2005; received a Ph.D. from the Hanoi University of Science and Technology (HUST) in 2013 and postdoctoral re- search at the University of Korea in 2014. Currently, he is a professor at HUST. Re- search Areas: Code Theory and Applications, Computer and Network Security, Wire- less Communication, Internet of Things. nguyendinhhan@gmail.com Article submitted 2020-01-03. Resubmitted 2020-06-12. Final acceptance 2020-06-13. Final version pub- lished as submitted by the authors. 42 http://www.i-jim.org ban.ptit@gmail.com nguyendinhhan@gmail.com