Static Nodes Research Articles

GPRS Sensor Node Battery Life Span Prediction Based on Received Signal Quality: Experimental Study

Nowadays with the evolution of Internet of Things (IoT), building a network of sensors for measuring data from remote locations requires a good plan considering a lot of parameters including power consumption. A Lot of communication technologies such as WIFI, Bluetooth, Zigbee, Lora, Sigfox, and GSM/GPRS are being used based on the application and this application will have some requirements such as communication range, power consumption, and detail about data to be transmitted. In some places, especially the hilly area like Rwanda and where GSM connectivity is already covered, GSM/GPRS may be the best choice for IoT applications. Energy consumption is a big challenge in sensor nodes which are specially supplied by batteries as the lifetime of the node and network depends on the state of charge of the battery. In this paper, we are focusing on static sensor nodes communicating using the GPRS protocol. We acquired current consumption for the sensor node in different locations with their corresponding received signal quality and we tried to experimentally find a mathematical data-driven model for estimating the GSM/GPRS sensor node battery lifetime using the received signal strength indicator (RSSI). This research outcome will help to predict GPRS sensor node life, replacement intervals, and dynamic handover which will in turn provide uninterrupted data service. This model can be deployed in various remote WSN and IoT based applications like forests, volcano, etc. Our research has shown convincing results like when there is a reduction of −30 dBm in RSSI, the current consumption of the radio unit of the node will double.

Performance analysis of chirp spread spectrum system under mobility scenario

A wireless communication system using Chirp Spread Spectrum Modulation (CSSM) is analyzed in this study while assuming mobile nodes. CSSM exhibits promising error performance under very low signal-to-noise ratio values. Thereby, CSSM has been adopted in systems that generate low data traffic over long distances, such as low-power wireless networks. Existing studies reveal the significant advantages of CSSM system assuming static nodes. Yet, this article extends the existing analysis by considering mobile nodes. In particular, the error performance of CSSM system under random waypoint mobility model and fading scenarios is investigated. Specifically, Rayleigh fading and Additive White Gaussian Noise (AWGN) channels along with one-dimensional (line), two-dimensional (circle), and three-dimensional (sphere) mobility conditions are considered. A closed-form expression for the average bit error rate (BER) of CSSM system is derived and thoroughly discussed. In addition, simplified asymptotic expressions are obtained for the derived average BER at pragmatic signal to noise ratio (SNR) values along with an approximate expressions assuming pure orthogonal spreading factors. Monte-Carlo simulations are provided to corroborate the accuracy of the conducted analysis, where close-match is reported for wide range of system and channel parameters. In addition, it is reported that distance has considerable impact on the performance, whereas higher mobility dimension induces negligible degradation in performance.

AC-RDV: a novel ant colony system for roadside units deployment in vehicular ad hoc networks

Vehicular ad hoc network (VANET) is a mobile and wireless network that consists of connected vehicles, and stationary nodes called roadside units (RSUs) placed on the aboard of roads to improve traffic safety and to ensure drivers’ and passengers’ comfort. However, deploying RSUs is one of the most important challenges in VANETs due to the involved placement, configuration, and maintenance costs in addition to the network connectivity. This study focuses on the issue of deploying a set of RSUs that is able to maximize network coverage with a reduced cost. In this paper, we propose a new formulation of RSUs deployment issue as a maximum intersection coverage problem through a graph-based modeling. Moreover, we propose a new bio-inspired RSU placement system called Ant colony optimization system for RSU deployment in VANET (AC-RDV). AC-RDV is based on the idea of placing RSUs within the more popular road intersections, which are close to popular places like touristic and commercial areas. Since RSU deployment problem is considered as NP-Hard, AC-RDV inspires by the foraging behavior of real ant colonies to discover the minimum number of RSU intersections that ensures the maximum network connectivity. After a set of simulations and comparisons against traditional RSU placement strategies, the results obtained showed the effectiveness of the proposed AC-RDV in terms of number of RSUs placed, the average area coverage, the average connectivity and the overlapping ratio.

A Fog Computing-Based Device-Driven Mobility Management Scheme for 5G Networks.

The fog computing-based device-driven network is a promising solution for high data rates in modern cellular networks. It is a unique framework to reduce the generated-data, data management overheads, network scalability challenges, and help us to provide a pervasive computation environment for real-time network applications, where the mobile data is easily available and accessible to nearby fog servers. It explores a new dimension of the next generation network called fog networks. Fog networks is a complementary part of the cloud network environment. The proposed network architecture is a part of the newly emerged paradigm that extends the network computing infrastructure within the device-driven 5G communication system. This work explores a new design of the fog computing framework to support device-driven communication to achieve better Quality of Service (QoS) and Quality of Experience (QoE). In particular, we focus on, how potential is the fog computing orchestration framework? How it can be customized to the next generation of cellular communication systems? Next, we propose a mobility management procedure for fog networks, considering the static and dynamic mobile nodes. We compare our results with the legacy of cellular networks and observed that the proposed work has the least energy consumption, delay, latency, signaling cost as compared to LTE/LTE-A networks.

Obstacle-Aware Connectivity Establishment in Wireless Sensor Networks

In wireless sensor networks (WSNs), the sensor nodes collect data from the target area and send it to the base station through a multi-hop connection. As a result, high energy dissipation of the sensor node may occur. Some times failure of nodes on large scale create partitions in the network. Also, the presence of obstacles is the reason for the coverage gap in networks. The introduction of mobile nodes has been measured to be a worthy approach to significantly decrease the energy dissipation of the static sensor nodes. This job is realized by considering the route through which the mobile collectors move to collect data from the sensor nodes. Another challenging job is to find the path of the mobile collector in an area with obstacles. In this work, an obstacle aware connectivity establishment (OACE) using mobile nodes in wireless sensor networks is proposed. The mobile robot collects data from each partition and carries forward to other partitions so data finally reaches to sink. To achieve this, a Delaunay triangulation based obstacle avoidance clustering has been performed. The performance of the proposed algorithm has been shown by varying the sensor nodes to a single mobile node and multiple mobile nodes. The number of partitions in the network also plays an important role in network performance. Simulation results show that the proposed method with multiple mobile collectors is more energy-efficient with less latency as compared to the single mobile collector for data collection.

Identification and eradication of attacker node in a mobile ad-hoc network environment using prediction model on delay factor

Mobile ad-hoc network (MANET) is a theoretical and experimental approach for achieving the applications to the best using VANETs. Given the mobility of nodes in the mobile ad-hoc networks, it is hard to depict the nature of the network or the structure of the network. With static nodes, it is easy to monitor a network. In a mobile environment, any node can come and join the network based on the distance covered by the entire network. A node that enters the region joins the network, while one that moves away leaves it and ceases participating in network communication. The routing table is updated, based on the movement of the nodes. Owing to the factors above, security fails to live up to expectations. Identifying a vulnerable node is a difficult proposition. This paper offers a prediction model based on the delay factor, which impacts the performance of the node and its network. The experimental results determine the malicious node. A malicious node is disconnected from the network.

CODE-V: Multi-hop computation offloading in Vehicular Fog Computing

Vehicular Fog Computing (VFC) is an extension of fog computing in Intelligent Transportation Systems (ITS). It is an emerging computing model that leverages latency-aware and energy-aware application deployment in ITS. In this paper, we consider the problem of multi-hop computation offloading in a VFC network, where the client vehicles are connected to fog computing nodes by multi-hop LTE access points. Our scheme addresses three key aspects in a VFC architecture namely: (i) Optimal decision on local or remote task execution, (ii) Optimal fog node assignment, and (iii) Optimal path (multi-hop) selection for computation offloading. Considering the constraints on service latency, hop-limit, and computing capacity, the process of workload allocation across host vehicles, stationary and mobile fog nodes, and the cloud servers is formulated into a multi-objective, non-convex, and NP-hard Quadratic Integer Problem (QIP). Accordingly, an algorithm named Computation Offloading with Differential Evolution in VFC (CODE-V) is proposed. For each client task, CODE-V takes into account inter-fog cooperation, fog node acceptance probability, and the topological variations in the transportation fleets, towards optimal selection of a target fog node. We conduct extensive simulations on the real-world mobility traces of Shenzhen, China, to show that CODE-V reduces the average service latency and energy consumption by approximately 28% and 61%, respectively, compared to the state-of-the-art. Moreover, the CODE-V also gives better solution quality compared to standard DE∕rand∕1∕bin algorithm and the solutions generated by a CPLEX solver.

An efficient data routing scheme for multi-patient monitoring in a biomedical sensor network through energy equalization strategy

Biomedical sensor networks find wide applications in human health monitoring. In such applications, routing strategies in the sensor nodes play a key role towards energy efficiency of the overall system. In this work, we present a new data routing scheme, which is based on residual energy in a node and equalization (named EEQ) among the neighbours to achieve enhanced average node lifetime under short range monitoring scenario. The scheme was hardware implemented using 12 number of indigenous ATmega328 based static biomedical sensor nodes (BSN) arranged in a grid matrix spread over a floor area of 564 sqm. The objective was to collect short duration electrocardiogram and photoplethysmogram signals from human subjects in a local supervisory computer placed outside the grid. Under simulation platform using 100 BSNs with first order radio model, it was found that the average node lifetime was enhanced by 17% against without EEQ evaluated over 10,000 consecutive data collection sessions. The proposed scheme can be useful for providing low cost solution in healthcare settings in developing nations like India.

Application of clockwise modularized laparoscopic lymphadenectomy in the suprapancreatic area, a propensity score matching study and comparison with open gastrectomy

BackgroundSuprapancreatic lymphadenectomy is the essence of D2 radical gastric cancer surgery. The present study aimed to describe clockwise modularized laparoscopic lymphadenectomy in the suprapancreatic area.MethodsThe data from gastric cancer patients who underwent surgical treatment from September 2016 to December 2018 were collected. Patients were divided into clockwise modularized lymphadenectomy (CML) and traditional open gastrectomy (OG) groups according to the surgical treatment strategy. The propensity score matching method was utilized to balance the baseline characteristics between the two groups.ResultsFinally, 551 gastric cancer patients were included in the present study. Following propensity score matching, 106 pairs of patients in the CML group and OG group were included in the final analysis. The CML group had more total examined lymph nodes (36, IQR 28–44.74 vs. 29, IQR 29–39.5, p = 0.002) and no. 9 station nodes (2, IQR 1–5 vs. 2, IQR 1–3, p = 0.007) than the OG group. There was less intraoperative blood loss (30, IQR 20–80 ml vs. 80, IQR 50–80 ml, p < 0.001) and a longer surgical duration (262.5 min, IQR 220–303.25 min vs. 232, IQR 220–255 min, p < 0.001) in the CML group than in the OG group. The incidence of postoperative complications (19.8% vs. 16.0%, p = 0.591) and postoperative hospital stay (8, IQR 7–9 days vs. 8, IQR 7–9 days, p = 0.452) were comparable between the CML and OG groups.ConclusionLaparoscopic lymphadenectomy for gastric cancer surgery is technically demanding. Clockwise modularized laparoscopic lymphadenectomy in the suprapancreatic area can attain similar effects as traditional open surgery and without an increase in postoperative adverse events.

Parameter Adaptation and Situation Awareness of LTE-R Handover for High-Speed Railway Communication

In the evolution of railway mobile communications from Long Term Evolution for Railway ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LTE-R</i> ) to the future 5th Generation Wireless System ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">5G</i> ), the rapid increase in the number of low-power base station nodes along the railway has brought more frequent handovers. The current handover parameter selection mechanism often relies on the on-site measured results in a limited number of discrete scenarios. It cannot deal with the continuous changing characteristics of the high-speed railway mobile communication environment, which leads to a serious lack of accuracy, adaptability and intelligence. This article hopes to construct a parameter-adaptive handover mechanism suitable for <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">5G</i> in the high-speed railway dedicated <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LTE-R</i> communication system. The mechanism first uses the interaction of Temporal-Difference( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">TD</i> )-learning-based reinforced agents to obtain high-speed railway handover performance and network performance in different combinations of speeds and handover parameters, and continuously updates the accumulated rewards used to target optimization, obtaining a Discrete TD value cube with closely related handover performance. Further, based on the Discrete TD value cube, we use the approximation function method for the completion of “continuous” situation of handover parameter selection, and construct a continuous TD value cube and the corresponding performance cubes. Our experimental results prove that TD learning agents with function approximation can accurately estimate and predict the handover performance and network performance of state combinations with different speeds and handover parameters, and further show that the handover parameter adaptation mechanism based on the Inference ability can find the optimal handover parameters to improve the handover performance and network performance.

Resilient Range-Based d-Dimensional Localization for Mobile Sensor Networks

Knowledge of node locations is essential to Wireless Sensor Networks (WSNs) in a wide range of potential applications and their function-dependent network protocols. A number of localization approaches have already been proposed to fulfill this requirement, but few of them can be applicable to mobile sensor networks, due to their low-dimensional embeddings, Euclidean distance representation limitations, frequent node mobility and additional measurement overhead in the network. In this paper, a resilient range-based $d$ -dimensional localization (RRDL) approach is proposed for mobile WSNs to resolve the issues. RRDL distinguishes itself from previous work with three remarkable characteristics: (1) it works for mobile networks embedded in $d$ -dimensional Non-Euclidean space; (2) it allows static ordinary nodes with pre-known locations to act as the alternative anchor nodes, thus tolerating the motion of the original anchor nodes to ensure that other ordinary nodes can obtain their locations in an efficient manner; and (3) it introduces an efficient path-learning approach, with the knowledge of the existing paths, to represent the real network distances as far as possible, thereby eliminating additional measurement overhead and tolerating node mobility in localization. With these characteristics, RRDL exploits the iterative factorization of the random distance matrix, formed by the distances to and from a set of $k$ -hop static neighbors, to assign each current node $d$ -dimensional Non-Euclidean coordinate in a distributed manner. Simulation results demonstrate that RRDL achieves higher localization accuracy with a moderate communication cost in mobile sensor networks.

A Beamforming Scheme With Doppler Suppression for High-Mobility Wireless Communications

In this letter, we consider the high-mobility wireless communications between a high speed train (HST) and a base station (BS) and propose a beamforming scheme with Doppler suppression for the stationary node BS. The typical Rician channel model is assumed, which occupies most of the HST communication scenarios. Based on the fact that the channel time-variation induces interference to the standard time-invariant signal model, the beamforming is then designed to maximize the signal-to-interference-plus-noise ratio (SINR) for both uplink and downlink transmissions. Simulation results are provided to verify that the channel time-variation can be effectively suppressed by the stationary BS through the proposed beamforming scheme.

Enhancing the Mobility Support in Internet of Things

Improving mobility support is a crucial task in low power and lossy networks (LLN). This article proposes an enhanced mobility support routing protocol (EM-RPL) to improve the mobility support for LLN. It has two processes, static node parent selection, and mobile node parent selection. The static node parent selection process uses the routing metrics, residual energy (RER), and load to choose the optimal parent for data transfer. The mobile node parent selection process has two phases, data transmission, and route discovery. Its handoff decision calculates from the received signal strength (RSSI) and packet error ratio (PER). The simulation is conducted using COOJA simulator. The performance of EM-RPL is compared with similar routing protocols. The simulation result shows that EM-RPL gives significant performance in terms of power consumption, latency, packet delivery ratio and packet overhead.

BSN MOT: A Fast and Cost-efficient Optoelectronic Architecture

Recently, an efficient recursive and symmetrical optoelectronic interconnection network based on biswapped framework named “Biswapped-Hyper Hexa-Cell (BSN HHC)” is reported. In spite of containing a prime advantage concerning network diameter compared to its competitive Biswapped-Mesh (BSN Mesh) optoelectronic architecture; a major limitation of the network is its high cost. In a search for a competitive alternative variation of this network, a fast and a cost-efficient member of biswapped family named “Biswapped-Mesh of Trees (BSN MOT)” is proposed here. The suggested BSN MOT optoelectronic network claims to be a better alternative of counter-part OTIS-Mesh of Trees (OTIS MOT) optoelectronic network, claims advantages concerning diameter, minimum node degree, and network total and optical cost (total cost drops about 10–30% and optical cost drops about 50%). More specifically, compared to competitive Biswapped-Mesh and BSN HHC optoelectronic networks, the proposed network has a major advantage concerning network diameter. Moreover, BSN MOT is a cost-efficient architecture, where total network cost drops about 30–45% than that of BSN HHC. Besides, it is a better alternative for processing numerical problems that require network with “low static maximum node degree”. Thus, on the basis of above-mentioned properties, the proposed network claims to be the most economical and the fastest variation of biswapped framework.

LDAP: Lightweight Dynamic Auto-Reconfigurable Protocol in an IoT-Enabled WSN for Wide-Area Remote Monitoring

IoT (Internet of Things)-based remote monitoring and controlling applications are increasing in dimensions and domains day by day. Sensor-based remote monitoring using a Wireless Sensor Network (WSN) becomes challenging for applications when both temporal and spatial data from widely spread sources are acquired in real time. In applications such as environmental, agricultural, and water quality monitoring, the data sources are geographically distributed, and have little or no cellular connectivity. These applications require long-distance wireless or satellite connections for IoT connectivity. Present WSNs are better suited for densely populated applications and require a large number of sensor nodes and base stations for wider coverage but at the cost of added complexity in routing and network organization. As a result, real time data acquisition using an IoT connected WSN is a challenge in terms of coverage, network lifetime, and wireless connectivity. This paper proposes a lightweight, dynamic, and auto-reconfigurable communication protocol (LDAP) for Wide-Area Remote Monitoring (WARM) applications. It has a mobile data sink for wider WSN coverage, and auto-reconfiguration capability to cope with the dynamic network topology required for device mobility. The WSN coverage and lifetime are further improved by using a Long-Range (LoRa) wireless interface. We evaluated the performance of the proposed LDAP in the field in terms of the data delivery rate, Received Signal Strength (RSS), and Signal to Noise Ratio (SNR). All experiments were conducted in a field trial for a water quality monitoring application as a case study. We have used both static and mobile data sinks with static sensor nodes in an IoT-connected environment. The experimental results show a significant reduction (up to 80%) of the number of data sinks while using the proposed LDAP. We also evaluated the energy consumption to determine the lifetime of the WSN using the LDAP algorithm.

A Privacy-Preserving Mobile and Fog Computing Framework to Trace and Prevent COVID-19 Community Transmission.

To slow down the spread of COVID-19, governments worldwide are trying to identify infected people, and contain the virus by enforcing isolation, and quarantine. However, it is difficult to trace people who came into contact with an infected person, which causes widespread community transmission, and mass infection. To address this problem, we develop an e-government Privacy-Preserving Mobile, and Fog computing framework entitled PPMF that can trace infected, and suspected cases nationwide. We use personal mobile devices with contact tracing app, and two types of stationary fog nodes, named Automatic Risk Checkers (ARC), and Suspected User Data Uploader Node (SUDUN), to trace community transmission alongside maintaining user data privacy. Each user's mobile device receives a Unique Encrypted Reference Code (UERC) when registering on the central application. The mobile device, and the central application both generate Rotational Unique Encrypted Reference Code (RUERC), which broadcasted using the Bluetooth Low Energy (BLE) technology. The ARCs are placed at the entry points of buildings, which can immediately detect if there are positive or suspected cases nearby. If any confirmed case is found, the ARCs broadcast pre-cautionary messages to nearby people without revealing the identity of the infected person. The SUDUNs are placed at the health centers that report test results to the central cloud application. The reported data is later used to map between infected, and suspected cases. Therefore, using our proposed PPMF framework, governments can let organizations continue their economic activities without complete lockdown.

Intersection Routing Based on Fuzzy Multi-Factor Decision for VANETs

Vehicular ad hoc network (VANET) is a special form of mobile ad hoc network (MANET), which plays a key role in the intelligent transportation system (ITS). Though many outstanding geographic routing protocols are designed for VANETs, a majority of them use parameters that only affect routing performance. In this article, we propose an intersection routing based on fuzzy multi-factor decision (IRFMFD), which utilizes several features. The scheme is divided into two parts, namely vehicular decision management and intersection decision management. In the vehicular component, candidate vehicles between two static nodes (SNs) located at two intersections derive potential routing paths considering distance, neighbor quantity, and relative velocity. In the intersection component, the candidate SN was chosen from the current intersection’s 2-hop neighbors which were connected with the current intersection by a route that was decided on in part one. To get the best scheme, we also introduced other factors to estimate the number of hops in each link and link lifetime. The simulation shows that the IRFMFD outperforms on delivery ratio and end-to-end delay compared with AODV (Ad hoc on-demand distance vector), GPSR (Greedy perimeter stateless routing) and GeOpps (Geographical opportunistic routing).

Multiple Transceivers for IEEE802.16 Mesh Network to Avoid Confusion Routing and Scheduling

The speed of data transfer and the amount of space within the communication service, taking into account the cost, security, capacity, and specifications of WiMAX is highly important in communications. There are varies difficulties for routing in WiMAX, for example, delay, long scheduling, interference and progressively stringent Quality of Service (QoS) backing and burden parity. This paper proposes a multi-transceiver and multi-channel centralized routing and scheduling algorithm to avoid the impact of packet collision with neighbor nodes. The proposed algorithm looks for a short path from the subscriber station (SS) node to Base station (BS), while the optimal path is achieved when the whole path has the lowest (energy bit minimum routing (EBMR)). After the route is fixed, and the traffic demanded at each node is known, the total traffic arriving at a node is centrally scheduled in order to avoid the transmission interferences. The results from the multi and nearest multi-transceiver systems showed that the proposed algorithm has effectively minimize the length of scheduling in the in multi nearest multi -transceiver system. Moreover, the channel utilization ratio (CUR) is found to be improved over the implementation of the proposed system

A Medium-Term Disruption Tolerant SDN for Wireless TCP/IP Networks

A novel framework, Medium-Term Disruption Tolerant Software Defined Network (MDT-SDN), is proposed to handle medium-term disruptions of the order 10 seconds to 6 minutes. Such medium-term disruptions are crucial for the next generation wireless networks that use TCP/IP protocol stack, where the existing disruption tolerant approaches may under-perform due to resource constraints. MDT-SDN enables network control with an additional STORE action which exploits the nodes’ memory for buffering packets within the TCP/IP stack during link disruptions and forwards them as the links become alive. First, we model the network with medium-term disruptions using temporal graphs and design an Earliest Arrival Path with Minimal Storage Time (EAPMST) controller algorithm to demonstrate the MDT-SDN framework. The framework is realized in a software defined wireless mesh network testbed, using in-band control, involving mobile nodes with three mobility models: ( ${i}$ ) stationary nodes, ( ii ) group mobility, and ( iii ) random mobility. Experimental results with four application protocols justify the efficacy of MDT-SDN in providing storage control and additional performance benefits. MDT-SDN along with EAPMST improves the throughput beyond 25% with random mobility model and is capable of carrying packets and maintaining sessions during medium-term disruptions using the existing TCP/IP stack. The use of EAPMST reduces packets’ buffering time by 24.45% in group mobility while the buffering time increases in random mobility by 5.82%. However, EAPMST significantly reduces the buffer occupancy by 60.28% and 44.49% for group and random mobility, respectively.

Optimization of disinfectant dosage for simultaneous control of lead and disinfection-byproducts in water distribution networks

Drinking water utilities are increasingly facing the challenges of maintaining water quality, and simultaneously complying with conflicting regulatory standards. One such challenge is the dosage of chlorine-based disinfectants which is typically regulated to prevent microbial growth in the water distribution systems, while limiting disinfection by-products (DBPs). On the other hand, chlorine residuals also influence the dissolution of lead into drinking water from corrosion scales in the pipe internals, as has been shown by previous studies. Hence, it is important to consider water lead levels (WLLs) while determining the appropriate chlorine dosage. This study proposes a multi-objective optimization framework to understand and balance the trade-offs between (i) minimizing total disinfectant dosage to reduce DBPs formation potential, and (ii) maximizing the volume of safe drinking water supply with respect to both WLLs and residual free chlorine concentrations. The approach comprises of the development of a dynamic simulation-optimization framework to account for the impact of spatial and temporal variations of network hydraulics and water chemistry on WLLs and residual free chlorine. The framework couples dynamic multi-species water quality simulations (pH, residual free chlorine, dissolved inorganic carbon, and orthophosphate concentration) with a multi-objective genetic optimization algorithm in an integrated MATLAB-EPANET-MSX platform. The application of the optimization formulation is demonstrated on a real-world distribution network case study. The resulting optimal solution set on pareto-plots are discussed for sensitivity of the trade-offs between the two objective functions, under various water chemistry conditions that have been suggested in earlier studies for minimizing lead release from plattnerite (PbO2) corrosion scales in lead service lines. The resulting optimal disinfectant dosage schedule, for pumping and booster station nodes in each case, provided insights on maintaining disinfectant residuals throughout the distribution system so as to prevent microbial growth as well as lead contamination events while limiting DBPs formation. Further, environmental implications related to the use of the proposed framework are also discussed.