Eliciting and Considering Underlay User Preferences for Data-Forwarding in Multihop Wireless Networks

Al-Shatri, Hussein; Keller, Katharina; Jacobfeuerborn, Fabian; Hinz, Oliver; Klein, Anja

doi:10.1109/access.2019.2906731

Cited by 3 publications

(5 citation statements)

References 33 publications

(42 reference statements)

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“…This experimental design is more realistic than traditional conjoint analyses due to the similarity of these choices to real-world decisions, so that CBCs explain actual adoption behavior well. CBCs with no-choice options are therefore a popular and frequently used survey method [44], [45]. One drawback is that when respondents select the nochoice option, we do not reveal any information about the trade-off between the attractiveness of the attribute levels in the product alternatives.…”

Section: A Research Methodologymentioning

confidence: 99%

“…Consequently, we simplify the technical dependencies and reduce them to generally applicable mechanisms. With this approach, we follow the methodology of [45] by simplifying the scenario to represent valid considerations of the impact on the network and users' devices but allow for a clear evaluation by all survey participants.…”

Section: B Study Setupmentioning

confidence: 99%

“…In this equation, vh,i is the utility of product i for consumer h and vh,0 is the utility of the no-choice option for consumer h. For the estimation of the individual-level parameters from the choice-based conjoint analysis data, we employ Hierarchical Bayes (HB). Based on the assumption of high consistency in decision making, HB is known to estimate part-worth very accurately for single attribute values, whereas a small number of choice sets per respondent is already sufficient (see, e.g., [45]). Accordingly, for the evaluation of our CBC experiment, we estimate the parameter values (see Table V) and derive the importance weights for the attributes of our study (see Fig.…”

Section: Cbc Analysismentioning

confidence: 99%

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Influence of Social Relationships on Decisions in Device-to-Device Communication

et al. 2021

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Device-to-device (D2D) communication is an innovative solution for improving wireless network performance to efficiently handle the ever-increasing mobile data traffic. Communication takes place directly between two devices that are in each other's transmission range. So far, research has focused on the technical challenges of implementing this technology and assumes a user's general willingness to participate as forwarder in this technology. However, this simplifying assumption is not realistic, as willingness to participate in D2D communication can vary depending on the user. In this work, we consider the scenario that a user can act as a forwarder for a receiver who is not directly or insufficiently reached by the base station and accordingly has no or poor Internet connection. We take a user-centric approach and investigate the willingness to provide an Internet connection as a forwarder. We are the first to investigate user preferences for D2D communication using a choice-based conjoint analysis. Our results, based on a representative sample of potential users (N=181), show that the social relationship between the potential forwarder and the receiver has the greatest impact on the potential forwarder's decision to provide an Internet connection to the receiver, accepting sacrifices in terms of additional battery consumption and reduced own service performance. In a detailed segment analysis, we observe significant preference differences depending on smartphone usage behavior and user age. Taking the corresponding preferences into account when matching forwarders and receivers can further increase technology adoption.

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Section: A Research Methodologymentioning

confidence: 99%

Section: B Study Setupmentioning

confidence: 99%

Section: Cbc Analysismentioning

confidence: 99%

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Influence of Social Relationships on Decisions in Device-to-Device Communication

et al. 2021

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“…Authors in [34] highlight the deficiency of an underlay network that it is designed without considering the importance of what a user of this network wants. Considering the importance of a user's preferences, authors propose a framework of a multihop network.…”

Section: Related Workmentioning

confidence: 99%

On Modeling Optimizations and Enhancing Routing Protocols for Wireless Multihop Networks

Al-Zahrani

2020

IEEE Access

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The contribution of this paper is two fold. It first analyses the flooding strategies for the Wireless Multihop Networks (WMNs) then it enhances the reactive and proactive routing protocols. For analysis purpose, we select four widely used flooding techniques for routing: i. traditional flooding, ii. Time-To-Live based Expanding Ring Search (TTL-based ERS) flooding scheme, iii. TTL-based Scope Routing (SR) flooding and iv. Multi-Point Relays (MPR) flooding. These techniques play a vital role and act as a backbone for routing protocols. Therefore, we compare efficiency of these techniques for six widely used routing protocols: Ad-hoc On-demand Distance Vector (AODV), Destination Sequenced Distance Vector (DSDV), Dynamic Source Routing (DSR), DYnamic MANET On-demand (DYMO), Fish-eye Scope Routing (FSR) and Optimized Link State Routing (OLSR). DSDV uses traditional flooding, AODV, DSR and DYMO use TTL-based ERS flooding, FSR uses TTL-based SR flooding and OLSR uses MPR flooding. This paper also presents mathematical models for flooding techniques and studies the affects of these techniques on their respective protocols in terms of energy and time consumption. This is done to measure the cost incurred by the routing protocols in the form of routing overhead and latencies. A novel contribution of this work is the enhancement in search set values and intervals of routing algorithms to improve the efficiency of selected existing protocols. A detailed comparison analysis of selected protocols with their default and enhanced routing algorithms in NS-2 is also a part of this work.INDEX TERMS Time-To-Live, expanding ring, destination sequenced distance vector, DYnamic MANET On-demand, ad-hoc on-demand distance vector, wireless multihop networks.

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“…The reason for taking such an approach for the second scenario is the importance of battery-life for the end-users. Studies show that energy consumption is one of the main concerns of the users when it comes to collaborative transmission [4]. Hence, in the second scenario, the transmitting nodes are also paid by their respective receiving nodes based on the power they use for serving their receivers.…”

Section: Introductionmentioning

confidence: 99%

Energy and Social Cost Minimization for Data Dissemination in Wireless Networks: Centralized and Decentralized Approaches

Mousavi

Klein

2020

IEEE Trans. Veh. Technol.

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We study multi-hop data-dissemination in a wireless network from one source to multiple nodes where some of the nodes of the network act as re-transmitting nodes and help the source in data dissemination. In this network, we study two scenarios; i) the transmitting nodes do not need an incentive and ii) they do need an incentive and are paid by their corresponding receiving nodes by virtual tokens. We investigate two problems; P1) network power minimization for the first scenario and P2) social cost minimization for the second scenario, defined as the total cost paid by the nodes of the network for receiving data. In this paper, we propose centralized and decentralized approaches for each of the problems. The proposed decentralized approach is based on a non-cooperative cost-sharing game (CSG). In our proposed game, every receiving node chooses its respective transmitting nodes and consequently, a cost is assigned to it according to the power imposed on its chosen transmitting nodes. For the sake of energy efficiency, in our model, we employ maximal-ratio combining (MRC) at the receivers so that a receiver can be served by multiple transmitters. Moreover, besides the radio-link power, we capture the power required by the passive modules of wireless devices involved in reception/transmission. We discuss how the network is formed in a decentralized way, find the actions of the nodes in the game and show that the proposed game reaches a Nash equilibrium. To find the centralized global optimum, which is a benchmark to our decentralized approach, we use a mixed-integer-liner-program (MILP). The proposed MILP can be used for both of the problems P1 and P2 with a minor change. Simulation results show that our proposed decentralized approach outperforms the conventional algorithms in terms of energy efficiency and social cost while it can address the need for an incentive for collaboration. 1

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Eliciting and Considering Underlay User Preferences for Data-Forwarding in Multihop Wireless Networks

Cited by 3 publications

References 33 publications

Influence of Social Relationships on Decisions in Device-to-Device Communication

Influence of Social Relationships on Decisions in Device-to-Device Communication

On Modeling Optimizations and Enhancing Routing Protocols for Wireless Multihop Networks

Energy and Social Cost Minimization for Data Dissemination in Wireless Networks: Centralized and Decentralized Approaches

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