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Nastooh Taheri Javan

Publications and source records attributed to Nastooh Taheri Javan.

12 recordsLinked to original sources

Mobility Enhancement of Patients Body Monitoring based on WBAN with Multipath Routing

One of the promising applications of wireless sensor networks (WSNs) is monitoring of the human body for health concerns. For this purpose, a large number of small sensors are implanted in the human body. These sensors altogether provide a network of wireless sensors (WBANs) and monitor the vital signs and signals of the human body; these sensors will then send this information to the doctor. The most important application of the WBAN is the implementation of the monitoring network for patient safety in the hospital environment. In this case, supporting patients' mobility is one of the basic needs, which has been underestimated in recent studies. The problem that involves providing the required energy for the units used in this type of network is challenging; for this reason, sent/received units with very low power consumption and with a very small radius are used in order to save energy. The resulting small sending range leads to the lack of support for patients' mobility. In this paper, the ad hoc mode is suggested for use to establish a network and a multipath routing algorithm for the purpose of supporting patients' mobility in a hospital setting. The results of the simulation show that, in addition to supporting patients' mobility, the use of the proposed idea instead of previously presented protocols reduces delays in data transmission and energy consumption; it also increases the delivery rate depending on the destination and the lifetime of the network, while increasing routing overhead.

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EDAP: An Efficient Data-Gathering Protocol for Wireless Sensor Networks

Directed Diffusion (DD), uses mechanisms such as data aggregation and in-network processing to suppress the additional data overhead however there is no guarantee that paths from nearby sources join after a few hops. Also for path construction, each source floods a distinct exploratory data (ED) packet through the network which is not necessary for nearby sources. In this paper an efficient data-gathering protocol (EDAP) is proposed to address the problems of late-aggregation and distinct ED-flooding through using a virtual sink (VS) node nearby the sources which plays the role of sink node and broadcasts local interest messages and routed gathered data toward destination. Also in this protocol, multiple paths are constructed between virtual sink and the sink node which leads to load-balancing and increase in the life-time of the network nodes. Our routing protocol can produce more than one disjoint or braided path and spread the gathered data properly between constructed paths according to their length and remaining energy. Simulation results shows that in this way a significant amount of energy can be saved and the network lifetime will be increased considerably (up to 75% better than DD).

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A Mobile Agent-Based Hierarchical Reinforcement Learning Framework for Energy-Balanced Data Collection and Wireless Charging in WSN

Energy imbalance remains a key challenge in Wireless Sensor Networks (WSNs), as nodes near the base station deplete their energy faster due to heavy forwarding loads. While mobile agents (MAs) have been employed for either data collection or sensor charging, existing approaches lack adaptability and fail to integrate both functions under realistic hardware constraints. This paper introduces a unified mobile agent framework that performs both data collection and wireless charging sequentially under single-antenna limitations. The agent's decision-making is formulated as a two-layer Hierarchical Reinforcement Learning (HRL) problem, where the upper layer optimizes movement planning and the lower layer determines the appropriate service based on real-time network states. This hierarchical structure enables the agent to learn adaptive task scheduling policies without predefined rules. Extensive simulations demonstrate that the proposed method achieves up to 15% longer network lifetime and more balanced energy distribution compared with state-of-the-art mobile agent and deep RL approaches.

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Adaptive Channel Hopping for IEEE 802.15.4 TSCH-Based Networks: A Dynamic Bernoulli Bandit Approach

In IEEE 802.15.4 standard for low-power low-range wireless communications, only one channel is employed for transmission which can result in increased energy consumption, high network delay and poor packet delivery ratio (PDR). In the subsequent IEEE 802.15.4-2015 standard, a Time-slotted Channel Hopping (TSCH) mechanism has been developed which allows for a periodic yet fixed frequency hopping pattern over 16 different channels. Unfortunately, however, most of these channels are susceptible to high-power coexisting Wi-Fi signal interference and to possibly some other ISM-band transmissions. This interference manifests itself in the form of the presence/absence of other devices with either or both static and dynamic channel selection policies. In order to isolate channels with undesirable conditions, blacklisting mechanisms are defined to adapt the channel hopping process. However, the existing solutions which form blacklists unrealistically assume that the statistical model of the external interference remains fixed, and do not vary over time. In this paper, we realistically assume that the impact of external interferes on 802.15.4 may generally follow a non-stationary pattern, and accordingly formulate the adaptive channel hopping problem as a Dynamic Multi-Armed Bernoulli Bandit (Dynamic MABB) process from the machine learning theory. We then propose an online learning algorithm with track-ability properties for computing an adaptive hopping policy. Simulations confirm that when the statistics of the external interference has a switching regime, the proposed solution outperforms the previous schemes in terms of both energy efficiency as well as two important KPIs for TSCH-based networks, i.e., PDR and latency.

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ZD-AOMDV: A New Routing Algorithm for Mobile Ad-Hoc Networks

A common characteristic of all popular multi-path routing algorithms in mobile ad-hoc networks, such as AOMDV, is that the end to end delay is reduced by utilization of parallel paths. The competition between the neighboring nodes for obtaining a common channel in those parallel paths is the reason for end to end delay increment. In fact, due to medium access mechanism in wireless networks, such as CSMA/CA, data transmissions even through two node-disjoint paths are not completely independent and each path will affect the other one. In this paper we have modified the AODV protocol which results in selection of zone-disjoint paths, to the extent feasible, and as a result we achieve less end to end delay. The efficiency of the proposed protocol has been evaluated on different scenarios and there has been a noticeable improvement in the packet delivery ratio and also in the reduction of end-to-end delay comparing to AOMDV.

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Trustworthy mobile edge caching: a blockchain approach to mitigate malicious nodes and incentivize cache sharing

As mobile network traffic continues to grow, content caching on edge servers is critical for reducing latency. However, challenges such as malicious edge servers that may delete or manipulate cached content, along with the limited capacity of these servers, need to be addressed. To overcome the capacity limitations, helper mobile nodes can contribute their cache resources. However, due to their selfish behavior, an incentive mechanism is necessary to encourage resource sharing. Additionally, these helper nodes can also be malicious. This paper proposes a blockchain-based trust management mechanism that addresses these challenges by accurately identifying trustworthy edge servers and mobile nodes. The proposed mechanism calculates both direct and indirect trust using smart contracts, ensuring that malicious nodes are effectively filtered out. Trustworthiness is determined based on mobile node satisfaction with the quality of service, and trust data is securely stored on the blockchain. To combat node selfishness, a reward mechanism is introduced to incentivize cache sharing. Furthermore, a blockchain-based authentication mechanism protects against node impersonation. Our approach optimizes trust, cache capacity, and cost efficiency while considering mobile node mobility, energy consumption, and computational power constraints during the consensus process. Simulation results show that the proposed method can accurately distinguish between honest and malicious servers, even with a 10% noise in data.

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Using Zone-Disjoint Multi-Path Routing Algorithm for Video Transmission over Ah-Hoc Networks

Finding multi-path routes in ad hoc networks due to their grid topology seems to be a trivial task, but because of CSMA/CA effects in these networks found paths are not completely disjoint unless an appropriate algorithm have taken into account. If such an algorithm provided and designed carefully it could improve multi-path video transmission over these kinds of networks. By using node-disjoint paths, it is expected that the end-to-end delay and BER in each case should be independent of each other. However, because of natural properties and medium access mechanisms in ad hoc networks the end-to-end delay and also BER between any source and destination depends on the pattern of communication in the neighborhood region. In this case some of the intermediate nodes should be silent to reverence their neighbors and this matter increases the end-to-end delay. To avoid this problem, multi-path routing algorithms can use zone-disjoint paths instead of node-disjoint paths. In this paper we demonstrated a new multi-path routing algorithm that selects zone-disjoint paths that in addition used for video multi-path transmission over ad hoc networks. It is shown that by using this new algorithm along with choosing an appropriate scheme for video transmission over discovered paths, our approach receives enhanced results comparing previously used algorithms.

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To Code or Not to Code: When and How to Use Network Coding in Energy Harvesting Wireless Multi-hop Networks

The broadcast nature of communication in transmission media has driven the rise of network coding's popularity in wireless networks. Numerous benefits arise from employing network coding in multi-hop wireless networks, including enhanced throughput, reduced energy consumption, and decreased end-to-end delay. These advantages are a direct outcome of the minimized transmission count. This paper introduces a comprehensive framework to employ network coding in these networks. It refines decision-making at coding and decoding nodes simultaneously. The coding-nodes employ optimal stopping theory to find optimal moments for packet transmission. Meanwhile, the decoding-nodes dynamically decide, through SMDP (Semi Markov Decision Process) problem formulation, whether to conserve energy by deactivating radio units or to stay active for improved coding by overhearing packets. The proposed framework, named ENCODE, enables nodes to learn how and when to use network coding over time. Simulation results compare its performance with existing approaches. Our simulation results shed new light on when and how to use network coding in wireless multi-hop networks more effectively.

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IEEE 802.15.4.e TSCH-Based Scheduling for Throughput Optimization: A Combinatorial Multi-Armed Bandit Approach

In TSCH, which is a MAC mechanism set of the IEEE 802.15.4e amendment, calculation, construction, and maintenance of the packet transmission schedules are not defined. Moreover, to ensure optimal throughput, most of the existing scheduling methods are based on the assumption that instantaneous and accurate Channel State Information (CSI) is available. However, due to the inevitable errors in the channel estimation process, this assumption cannot be materialized in many practical scenarios. In this paper, we propose two alternative and realistic approaches. In our first approach, we assume that only the statistical knowledge of CSI is available a priori. Armed with this knowledge, the average packet rate on each link is computed and then, using the results, the throughput-optimal schedule for the assignment of (slot-frame) cells to links can be formulated as a max-weight bipartite matching problem, which can be solved efficiently using the well-known Hungarian algorithm. In the second approach, we assume that no CSI knowledge (even statistical) is available at the design stage. For this zero-knowledge setting, we introduce a machine learning-based algorithm by formally modeling the scheduling problem in terms of a combinatorial multi-armed bandit (CMAB) process. Our CMAB-based scheme is widely applicable to many real operational environments, thanks to its reduced reliance on design-time knowledge. Simulation results show that the average throughput obtained by the statistical CSI-based method is within the margin of 15% from the theoretical upper bound associated with perfect instantaneous CSI. The aforesaid margin is around 18% for our learning-theoretic solution.

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To overhear or not to overhear: a dilemma between network coding gain and energy consumption in multi-hop wireless networks

Any properly designed network coding technique can result in increased throughput and reliability of multi-hop wireless networks by taking advantage of the broadcast nature of wireless medium. In many inter-flow network coding schemes nodes are encouraged to overhear neighbours traffic in order to improve coding opportunities at the transmitter nodes. A study of these schemes reveal that some of the overheard packets are not useful for coding operation and thus this forced overhearing increases energy consumption dramatically. In this paper, we formulate network coding aware sleep/wakeup scheduling as a semi Markov decision process (SMDP) that leads to an optimal node operation. In the proposed solution for SMDP, the network nodes learn when to switch off their transceiver in order to conserve energy and when to stay awake to overhear some useful packets. One of the main challenges here is the delay in obtaining reward signals by nodes. We employ a modified Reinforcement Learning (RL) method based on continuous-time Q-learning to overcome this challenge in the learning process. Our simulation results confirm the optimality of the new methodology.

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To Send or Not to Send: An Optimal Stopping Approach to Network Coding in Multi-hop Wireless Networks

Network coding is all about combining a variety of packets and forwarding as much packets as possible in each transmission operation. The network coding technique improves the throughput efficiency of multi-hop wireless networks by taking advantage of the broadcast nature of wireless channels. However, there are some scenarios where the coding cannot be exploited due to the stochastic nature of the packet arrival process in the network. In these cases, the coding node faces two critical choices: forwarding the packet towards the destination without coding, thereby sacrificing the advantage of network coding, or, waiting for a while until a coding opportunity arises for the packets. Current research works have addressed this challenge for the case of a simple and restricted scheme called reverse carpooling where it is assumed that two flows with opposite directions arrive at the coding node. In this paper the issue is explored in a general sense based on the COPE architecture requiring no assumption about flows in multi-hop wireless networks. In particular, we address this sequential decision making problem by using the solid framework of optimal stopping theory, and derive the optimal stopping rule for the coding node to choose the optimal action to take, i.e. to wait for more coding opportunity or to stop immediately (and send packet). Our simulation results validate the effectiveness of the derived optimal stopping rule and show that the proposed scheme outperforms existing methods in terms of network throughput and energy consumption.

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Improving Energy Efficiency in MANETs by Multi-Path Routing

Some multi-path routing algorithm in MANET, simultaneously send information to the destination through several directions to reduce end-to-end delay. In all these algorithms, the sent traffic through a path affects the adjacent path and unintentionally increases the delay due to the use of adjacent paths. Because, there are repetitive competitions among neighboring nodes, in order to obtain the joint channel in adjacent paths. The represented algorithm in this study tries to discover the distinct paths between source and destination nodes with using Omni directional antennas, to send information through these simultaneously. For this purpose, the number of active neighbors is counted in each direction with using a strategy. These criterions are effectively used to select routes. Proposed algorithm is based on AODV routing algorithm, and in the end it is compared with AOMDV, AODVM, and IZM-DSR algorithms which are multi-path routing algorithms based on AODV and DSR. Simulation results show that using the proposed algorithm creates a significant improvement in energy efficiency and reducing end-to-end delay.

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