Message Cost Research Articles

Load-aware switch migration for controller load balancing in edge–cloud architectures

As the fundamental infrastructure for edge–cloud architectures, the inter-datacenter elastic optical network is used for data analysis and processing. As the demand for applications increases, the large number of service requests increases the processing overhead in the control plane, resulting in unbalanced controller loads. Existing switch migration mechanisms have been proposed for controller load balancing. Unfortunately, most of the existing mechanisms only consider the switch with the highest flow request rate as the migration object in the process of switch selection, and ignore the migration cost generated in the switch migration activity, such as the update cost of flow request message and the deployment cost of migration rule, which may increase the controller load. Additionally, most of them choose the controller with light load as the target controller to associate with the switch to be migrated, without considering whether the target controller is overloaded after the switch migration, which leads to the low load balancing performance of the controller. In view of the above problems, this paper proposes a Load-Aware Switch Migration (LASM) mechanism in edge–cloud architectures. The LASM mechanism models and analyses the cost metrics affecting switch migration and selects lower-cost switches from overloaded controller-controlled domain networks for migration activities. Besides, the LASM mechanism models switch migration based on the 0-1 knapsack problem and avoids overloading the target controllers through a greedy policy to achieving optimal migration activities. The experimental results show that the proposed LASM mechanism improves controller load balancing performance by an average of 34.3%, eliminates migration costs by 30.2%, and reduces response times by an average of 39.3%, respectively, compared to existing solutions.

Perbandingan Metode EOQ, JIT, Kebijakan Perusahaan dalam Pengendalian Biaya Persediaan Bahan Baku pada Loske Coffeeshop

Coffeshop Loske is a business of the food and beverage industry, the problem with the Loske Coffeeshop is whether its current supply of raw materials is efficient and whether its EOQ method and its effective effective is in the Loske Coffeeshop. The purpose of the study is to analyze the optimum cost of supply of raw materials on the Loske Coffeeshop and to find out if EOQ methods and JIT can optimize the control of supply of raw materials in the Loske Coffeeshop. The data needed is a general picture of Loske Coffeeshop, organization structure, production process, raw materials supply data, raw materials use data, message cost data, and store cost data. A data-collection technique using a documentary method. Based on studies already done, researchers concluded that the EOQ method and JIT method were proven to optimize the cost of controlling the supply of raw materials when applied to the loske coffeeshop. EOQ methods produced a supply charge of Rp 9.998.749, and the JIT method produced a supply cost of Rp 10.203.373, whereas using the company's policy method currently used produces a stock cost of Rp 14.404.302.

The Reach of Calls and Text Messages for Mailed FIT Outreach in the PROMPT Stepped-Wedge Colorectal Cancer Screening Trial.

Mailed fecal immunochemical test (FIT) outreach can improve colorectal cancer screening participation. We assessed the reach and effectiveness of adding notifications to mailed FIT programs. We conducted secondary analyses of a stepped-wedge evaluation of an enhanced mailed FIT program (n = 15 clinics). Patients were stratified by prior FIT completion. Those with prior FIT were sent a text message (Group 1); those without were randomized 1:1 to receive a text message (Group 2) or live phone call (Group 3). All groups were sent automated phone call reminders. In stratified analysis, we measured reach and effectiveness (FIT completion within 6 months) and assessed patient-level associations using generalized estimating equations. Patients (n = 16,934; 83% Latino; 72% completed prior FIT) were reached most often by text messages (78%), followed by live phone calls (71%), then automated phone calls (56%). FIT completion was higher in patients with prior FIT completion versus without [44% (Group 1) vs. 19% (Group 2 + Group 3); P < 0.01]. For patients without prior FIT, effectiveness was higher in those allocated to a live phone call [20% (Group 3) vs. 18% (Group 2) for text message; P = 0.04] and in those who personally answered the live call (28% vs. 9% no call completed; P < 0.01). Text messages reached the most patients, yet effectiveness was highest in those who personally answered the live phone call. Despite the broad reach and low cost of text messages, personalized approaches may more successfully boost FIT completion.

A Novel Hierarchical Security Solution for Controller-Area-Network-Based 3D Printing in a Post-Quantum World.

As the popularity of 3D printing or additive manufacturing (AM) continues to increase for use in commercial and defense supply chains, the requirement for reliable, robust protection from adversaries has become more important than ever. Three-dimensional printing security focuses on protecting both the individual Industrial Internet of Things (I-IoT) AM devices and the networks that connect hundreds of these machines together. Additionally, rapid improvements in quantum computing demonstrate a vital need for robust security in a post-quantum future for critical AM manufacturing, especially for applications in, for example, the medical and defense industries. In this paper, we discuss the attack surface of adversarial data manipulation on the physical inter-device communication bus, Controller Area Network (CAN). We propose a novel, hierarchical tree solution for a secure, post-quantum-supported security framework for CAN-based AM devices. Through using subnet hopping between isolated CAN buses, our framework maintains the ability to use legacy or third-party devices in a plug-and-play fashion while securing and minimizing the attack surface of hardware Trojans or other adversaries. The results of the physical implementation of our framework demonstrate 25% and 90% improvement in message costs for authentication compared to existing lightweight and post-quantum CAN security solutions, respectively. Additionally, we performed timing benchmarks on the normal communication (hopping) and authentication schemes of our framework.

Endogenous ambiguity and rational miscommunication

This paper studies a sender-receiver game in which both players want the receiver to choose the state-optimal action. Before observing the state, the sender observes a “contextual signal,” a payoff-irrelevant signal that correlates with states and is imperfectly shared with the receiver. Once the sender observes the state, the sender sends a message to the receiver, incurring a small messaging cost. It is shown that there is no miscommunication in any efficient equilibrium if the messaging cost is uniform or contextual information is poorly shared between players. However, if the messaging costs are different between some messages, and contextual information can affect the probability ranking of states and is shared reasonably well, any efficient equilibrium that favors the sender exhibits miscommunication. Furthermore, the messages that cause miscommunication can be coarse or ambiguous, depending on how well players share contextual information.

Energy‐aware redundancy‐aware clustering in wireless sensor networks using Spined Loach Searching Optimization

SummaryWireless sensor networks play dominant role in data communication in many engineering applications and faces lot of challenges in its implementation. Energy conservation is also significantly required in these systems as the sensor nodes are battery operated. Hence, the energy efficient‐based technique needs to be implemented in data transmission. The most widely used methods are clustering‐based data transmission and energy efficient routing detection. In clustering, the proper selection of cluster head (CH) node is important to ensure energy balancing. The CH node should have more residual energy as it does many transmissions in the network. Moreover, the location of CH node should be nearer to all member nodes in the cluster. The clustering process must also perform the job of avoiding unnecessary transmissions. By considering these factors, the CH node can be optimally selected using Spined Loach Searching Optimization algorithm. The food searching behavior and environmental suitability for spiny loach fish living are deliberated to develop this bio‐inspired algorithm. In addition, the redundant transmissions inside the clusters can be reduced by employing a new technique called Least Difference Threshold Based Similarity Grouping. This work improves energy efficiency comparing with the conventional low energy adaptive clustering hierarchy protocol, and it is evaluated by setting the network in simulation environment. The network lifetime is increased; energy consumption, delay of transmission and the message cost are reduced.

A Method to Deliver Automated and Tailored Intervention Content: 24-month Clinical Trial.

BackgroundThe use of digital technologies and software allows for new opportunities to communicate and engage with research participants over time. When software is coupled with automation, we can engage with research participants in a reliable and affordable manner. Research Electronic Data Capture (REDCap), a browser-based software, has the capability to send automated text messages. This feature can be used to automate delivery of tailored intervention content to research participants in interventions, offering the potential to reduce costs and improve accessibility and scalability.ObjectiveThis study aimed to describe the development and use of 2 REDCap databases to deliver automated intervention content and communication to index participants and their partners (dyads) in a 2-arm, 24-month weight management trial, Partner2Lose.MethodsPartner2Lose randomized individuals with overweight or obesity and cohabitating with a partner to a weight management intervention alone or with their partner. Two databases were developed to correspond to 2 study phases: one for weight loss initiation and one for weight loss maintenance and reminders. The weight loss initiation database was programmed to send participants (in both arms) and their partners (partner-assisted arm) tailored text messages during months 1-6 of the intervention to reinforce class content and support goal achievement. The weight maintenance and reminder database was programmed to send maintenance-related text messages to each participant (both arms) and their partners (partner-assisted arm) during months 7-18. It was also programmed to send text messages to all participants and partners over the course of the 24-month trial to remind them of group classes, dietary recall and physical activity tracking for assessments, and measurement visits. All text messages were delivered via Twilio and were unidirectional.ResultsFive cohorts, comprising 231 couples, were consented and randomized in the Partner2Lose trial. The databases will send 53,518 automated, tailored text messages during the trial, significantly reducing the need for staff to send and manage intervention content over 24 months. The cost of text messaging will be approximately US $450. Thus far, there is a 0.004% known error rate in text message delivery.ConclusionsOur trial automated the delivery of tailored intervention content and communication using REDCap. The approach described provides a framework that can be used in future behavioral health interventions to create an accessible, reliable, and affordable method for intervention delivery and engagement that requires minimal trial-specific resources and personnel time.Trial RegistrationClinicalTrials.gov NCT03801174; https://clinicaltrials.gov/ct2/show/NCT03801174?term=NCT03801174

LBlockchainE: A Lightweight Blockchain for Edge IoT-Enabled Maritime Transportation Systems

Blockchain can help edge IoT-enabled Maritime Transportation Systems (MTS) in solving its privacy and security problems. In this paper, a lightweight blockchain called LBlockchainE is designed for edge IoT-enabled MTS to guarantee the security of sensor data stored in an edge computing environment. To save the resources of edge servers on ship, a data placement strategy is proposed. To encourage edge servers to positively contribute to storing data generated by sensor devices, storage resource consumption is employed as an influencing parameter, and servers with abundant resources are selected for priority storage. The data placement strategy also takes care of the access delay between servers and selects the nodes with the least access and storage costs as the priority storage choice. LBlockchainE applies the low-energy-consumption characteristics of Proof of Stake to determine the ownership of bookkeeping rights through a small number of competitive calculations and the resources of the node. Experimental results indicate that compared with Ethereum, the consensus mechanism of LBlockchainE consumes less energy and occupies less storage space. On average, the new system uses 1.6% less time and consumes 78% less battery power compared with traditional blockchain systems. In comparison to the random storage, the best storage, and the optimal data storage strategies, the proposed strategy maintains the same message costs.

A Provably Secure and Efficient Remote Password Authentication Scheme Using Smart Cards

Communication technology has advanced dramatically amid the 21^st century, increasing the security risk in safeguarding sensitive information. The remote password authentication (RPA) scheme is the simplest cryptosystem that serves as the first line of defence against unauthorised entity attacks. Although the literature contains numerous RPA schemes, to the best of the authors’ knowledge, only few schemes based on the integer factorisation problem (IFP) and the discrete logarithm problem (DLP) that provided a provision for session key agreement to ensure proper mutual authentication. Furthermore, none of the previous schemes provided formal security proof using the random oracle model. Therefore, this study proposed an improved RPA scheme with session key establishment between user and server. The design of the proposed RPA scheme is based on the widely established Dolev-Yao adversary model. Moreover, as the main contribution, a novel formal security analysis based on formal definitions of IFP and DLP under the random oracle model was presented. The proposed scheme's performance was compared to that of other similar competitive schemes in terms of the transmission/computational cost and time complexity. The findings revealed that the proposed scheme required higher memory storage costs in smart cards. Nonetheless, the proposed scheme is more efficient regarding the transmission cost of login and response messages and the total time complexity compared to other scheme of similar security attributes. Overall, the proposed scheme outperformed the other RPA schemes based on IFP and DLP. Finally, the potential application of converting the RPA scheme to a user identification (UI) scheme is considered for future work. Since RPA and UI schemes are similar, the proposed approach can be expanded to develop a provably secure and efficient UI scheme based on IFP and DLP.

A Mobility Management Algorithm in the Internet of Things (IoT) for Smart Objects based on Software-Defined Networking (SDN)

In recent decades, technological advancements have significantly improved people's living standards and given rise to the rapid development of intelligent technologies. The Internet of Things (IoT) is one of the most important research topics worldwide. However, IoT is often comprised of unreliable wireless networks, with hundreds of mobile sensors interconnected. A traditional sensor network typically consists of fixed sensor nodes periodically transmitting data to a pre-determined router. Current applications, however, require sensing devices to be mobile between networks. We need mobility management protocols to manage these mobile nodes to provide uninterrupted service to users. The interactions between the mobile nodes are affected by the loss of signaling messages, increased latency, signaling costs, and energy consumption because of the characteristics of these networks, including constrained memory, processing power, and limited energy source. Hence, developing an algorithm for managing smart devices' mobility on the Internet is necessary. This study proposes an efficient and effective distributed mechanism to manage mobility in IoT devices. Using Software-Defined Networking (SDN) based on the CoAP protocol, the proposed method is intended not only to reduce the signaling cost of messages but also to make mobility management more reliable and simpler.

Autoregressive moving average based anycast with support vector machine clustering in mobile ad‐hoc networks

AbstractNodes in mobile ad‐hoc networks (MANETs) are battery‐powered, therefore, need energy‐efficient techniques to cut down the cost of energy consumption. Energy consumption is directly related to route discovery, which could be reduced through anycasting. Anycast is an operation in MANETs, where the source sends messages to one particular destination node of anycast region. In general, the message transmitted is divided into certain packets, and those are transmitted continuously one after the other through selected routes. If the link from anycast source to destination breaks in between or an anycast destination goes out of the anycast region, in that case, a new anycast destination will have to be selected on a new route to the destination. This will incur huge message costs and energy. In this work, we select desirable anycast destinations based on their eligibility by using autoregressive moving average and support vector machine. Eligibility is modeled as a function of residual energy, location, the relative velocity concerning neighbors, and the number of packets successfully forwarded earlier by those neighbors' locations. Reducing the number of anycast receivers reduces the message cost of protocols significantly. We have compared our protocol's performance with the same of anycast‐AODV, anycast‐DSR, anycast‐FAIR, and MQAR (mobility and QoS‐aware anycast routing protocol) results show significant improvement. Collective improvement amounts to 89% more energy preservation and 39% delay on average.

Risk of Cancer and Cost of Surgery Outweigh Urgency and Messaging in Hypothetical Decisions to Remove Tumors

Risk of Cancer and Cost of Surgery Outweigh Urgency and Messaging in Hypothetical Decisions to Remove Tumors

Entropy based TOPSIS method for controller selection in software defined networking

SummarySoftware defined networking (SDN) architecture is easily manageable, flexible, and dynamic where controller selection plays a major role. In SDN, the controlling functions are handled by control plane and forwarding functions are handled by data plane. In general, the centralized controller supervises the control plane, and it communicates with the data plane using “Open Flow” (south bound interface). Moreover, OpenFlow based controllers such as POX, Floodlight, Beacon, and RYU have different features which suit different applications in real time. In this proposed work, a multi‐criteria decision making method named entropy based TOPSIS method is used to select the controller for load balancing in control plane. Initially, four controllers are selected and evaluated over tree topology with different parameters such as throughput, delay, response time, message cost using the network emulator called Mininet. Then, entropy based TOPSIS method is used to rank the controllers where Floodlight is chosen as the most excellent one based on our criteria.

Bus-Based VANET using ACO Multipath Routing Algorithm

Vehicular ad-hoc Network (VANET) for buses provides a good solution with inconsistent and high dynamic structure of a typical network. In this work, Street-centric routing algorithm is used for internet of energy for the bus-based VANET to optimize relay bus and route selection issues. As the initial step, we have used a multipath routing system that uses probability of path consistency and street consistency. This methodology is observed to positively improve end-to-end delay and also the packet delivery ratio. The next step is to optimize the characteristics of packet forwarding by means of an Ant Colony Optimization (ACO) methodology as the mechanism for relay-bus selection. The main goal of this paper is to transmit packets to the next forwarding relay with the help of relay-bus. On experimental analysis, the results indicate that there is a significant improvement in relay-bus choosing by reducing the end-to-end delay, cost of computation and unwanted beacon messages. Based on the analysis, we have arrived at the conclusion that the use of clustering and multipath will positively improve the performance of the proposed work.

Minimum energy transmission forest‐based geocast in software‐defined wireless sensor networks

AbstractWireless Sensor Networks (WSNs)‐based geographic addressing and routing have many potential applications. Geocast protocols should be made energy efficient to increase the lifetime of nodes and packet delivery ratio. This technique will increase the number of live nodes, reduce message costs, and enhance network throughput. All geocast protocols in the literature of WSN apply mostly restricted flooding and perimeter flooding, which is why still the redundancy they produce significantly high message transmission costs and unnecessarily eats up immense energy of the nodes. Moreover, perimeter flooding cannot succeed in the presence of holes. The present article models WSN with software‐defined (SD) constructs where the network area is divided into some zones. Energy‐efficient transmission tree(s) are constructed in the geocast area to organize the flow of data packets and their links. Therefore, redundancy in the transmission is eliminated while maintaining network throughput as good as regular flooding. Besides, this study introduces a fuzzy controllers named SELECT‐STARTER and GEOCAST‐PROPAGATOR for intellgent energy tansmission control‐making. The proposed technique significantly reduces energy cost and improves nodes' lifetime to function for higher time duration and produce a higher data packet delivery ratio. To the best of the author's knowledge, this is the first work on geocast in SD‐WSNs.

Optimizing costs for vaccine control using the reorder point approach

Vaccines are biological products that have an important role in human immunity. In Indonesia, some vaccines are categorized as compulsory vaccines and additional vaccines. The demand for additional vaccines is less predictable because they are not mandatory for use. This of course makes the amount of demand for vaccines less predictable. Also, the price of additional vaccines is not cheap when compared to the price of mandatory vaccines. So that the management of vaccines in the pharmacy warehouse is needed so that the amount of supply and demand is balanced so that the costs incurred will be more optimal. The information system regarding vaccine reordering is carried out using a reorder point so that the pharmacy warehouse can order according to the right need and at the right time. The data used are demand data, prices, storage costs, and message costs. The results of calculations using reorder points within four months with a total purchase for the Rotavirus vaccine was 62 for IDR 28,274,948 and 70 for the hospital of IDR 31,801,500 with a difference of IDR 3,528,552. The calculation result using the reorder point for the Hexaxim vaccine with a total purchase for 4 months was 61 with a nominal value of IDR 58,380,060 while the calculation in the hospital was 67 with a nominal value of IDR 63,971,000 so that a nominal difference of IDR 5,590,940 was obtained. Use of the return point can be used to alarm when and how many vaccines to order. This can be seen from the cost difference between the pharmacy warehouse and the calculation using the reorder point for the Hexaxim vaccine and the Rotavirus vaccine.

ARMA Model Based Anycast AODV (ARMA-AAODV) for Performance Improvement in Scalable Mobile Ad Hoc Networks

Anycast is a special operation in ad hoc networks, where source communicates with one suitable destination in anycast zone. AAODV or anycast ad hoc on demand distance vector is an anycast routing protocol designed as an extension of AODV protocol to enable any cast operation in ad hoc networks. However, requirement of stability comes to existence where a huge number of data packets are to be transmitted from anycast source to anycast zone. If source elects one particular peripheral node of the anycast zone and the peripheral anycast destination goes out of the specified zone after receiving only a few number of packets , then source has to again broadcast route requests leading to huge message cost in the network. In our present work, we predict the presence of selected peripheral destination in anycast zone based on its history of location and velocity in earlier time stamps, which is used during route selection in AAODV. Also flooding of route request is directional based on coordinates of anycast zone supplied to the source. This helps to restrain flooding of route request within a limited portion of network.

Novel congestion avoidance scheme for Internet of Drones

Internet of Drones (IoDs) is getting growing interest of researchers due to its applicability in wide range of applications for transportation, weather monitoring, emergency monitoring for flood, earth quake, healthcare and road hazards. To update the data about emergency situation, a real-time data sharing is mandatory. However, regular message transmission by various drones may not only overwhelm a central server but it also causes congestion on the network. It is mandatory to reduce messaging cost and congestion. This paper presents a fog-assisted congestion avoidance approach for Smooth Message Dissemination (SMD). We present a message forwarding algorithm for congestion avoidance to select the appropriate next-hop node using layered model. This model is based on various layers having drones. In first phase, it looks for an appropriate drone in a layer near the fog server for message forwarding. In next step, the drone is identified in nearby layers to forward the emergency message to next-hop to further locate the group head as per priority. It is a drone that has less distance towards fog server and inform in its one-hop circle. It can stop forwarding message after delivering it to fog server. Finally, the fog server disseminates information timely towards upper layers for necessary actions for emergency situations. The performance of the proposed approach is validated through extensive simulations using NS 2.35. Results prove the dominance of SMD over counterparts in terms of messaging overhead, packet delivery ratio, throughput, energy consumption and average delay. Proposed SMD improves PDR by 85% and message overhead cost by 91% as compared to counterparts.

MROM Scheme to Improve Handoff Performance in Mobile Networks

Mobile Router (MR) mobility supported by Network Mobility Basic Support Protocol (NEMO BS) is a Mobile IPv6 (MIPv6) extension that supports Host Mobility. Proposed Multihoming and Route Optimization for MANEMO (MROM) scheme is designed to provide Route Optimization (RO) and Multihomed in NEMO architectures. This paper proposes two novel schemes; MANEMO routing scheme and Multihoming-based scheme. These are to provide support for next generation networks. The proposed MROM scheme differs from other schemes for NEMO environment because it considers the requirements of more application flows parameters as packet lost delivery, handoff delay as well as throughput). Another difference is that not only the network infrastructure can begin the functionality of flow routing, but also an Edge Mobile Router (EMR) can do this flow for routing. Moreover, it utilizes the state of the art and presently active access network to perform the separation of each flow in mobile network. Thus, proposed MROM exhibits multihoming features and improves handoff performance by initiating flow-based fast registration process in NEMO environment. A handoff method is proposed with enhanced functionalities of the Local Mobility Anchors (LMA), Mobile Routers (MRs) and signaling messages with a view to achieve continuous connectivity through handoff in NEMO. Both analytical and simulation approaches are used. Analytical evaluation is carried out to analyze packet delivery lost and handoff delay of our proposed scheme. It was also shown that cost of signaling messages and packet delivery are contributing to total handoff cost. At the simulation part, network simulator 3 (NS 3) has been used as the tool to get performance metrics that have been considered like packet delivery ratio, handoff delay, and packet loss. Our proposed scheme (MROM) has been benchmarking to the standard NEMO BS Protocol and P-NEMO. In this paper, we discuss proposed MROM for next generation networks, providing detailed analysis with a numerical model, proposed MROM, by maximizing the handoff performance, has been justified to have better mobility support than the ordinary NEMO BS Protocol and PNEMO.

Efficient Scheduling, Caching, and Merging of Notifications to Save Message Costs in IoT Networks Using CoAP

Internet-of-Things (IoT) devices are widely deployed and many of them have limited capabilities. Constrained application protocol (CoAP) is developed to integrate such devices into the Web environment. Specifically, client devices register their interested data with IoT devices, which will keep notifying them of the status of sensing data. However, client devices have different demands in terms of minimum and maximum periods to receive notifications, whereas IoT devices usually offer notifications at regular intervals. Some IoT devices would send many more notifications than necessary, which wastes bandwidth and energy. To conquer this problem, this article proposes a group-based message management (GMM) framework for CoAP proxies to efficiently coordinate the sending of notifications from IoT devices and forward them to client devices. GMM curtails superfluous notifications by three modules. The scheduling module groups client devices based on their demands and finds an optimal observation period for each group. The caching module adjusts the max-age value to allow a proxy reusing its cached notifications to answer requests. The merging module combines the notifications originated from different IoT devices queried by the same client device so as to save bandwidth. The simulation results show that GMM not only reduces unnecessary notifications but also conserves the energy of devices.