Epidemic routing (Flooding) is considered as a simple routing protocol for opportunistic networks where the participants attempt to transmit whatever information they have to everyone who does not already have that in...Epidemic routing (Flooding) is considered as a simple routing protocol for opportunistic networks where the participants attempt to transmit whatever information they have to everyone who does not already have that information. However, it is plagued with disadvantages of resource scarcity as it exerts stress on available bandwidth as well as storage capacity of the devices in the network. Cognitive radio (CR) is one of the emerging technologies that can improve the bandwidth utilization by smart allocation of spectrum radio bands. Ideally speaking, a spectrum-aware cognitive radio is able to sense the local spectrum usage and adapt its own radio parameters accordingly. In this study, we have performed experiments to analyze the gains achieved by flooding protocol using cognitive radios of varying capabilities in opportunistic networks. We have performed experiments on three opportunistic networks obtained from real-life traces from different environments and presented results showing variance in delivery efficiency as well as cost incurred on those scenarios. Our results show that performance of flooding can be significantly improved using CRs in bandwidth-scarce environments;however, the improvement is not uniform with the increase in a number of available bands.展开更多
Most of the existing opportunistic network routing protocols are based on some type of utility function that is directly or indirectly dependent on the past behavior of devices. The past behavior or history of a devic...Most of the existing opportunistic network routing protocols are based on some type of utility function that is directly or indirectly dependent on the past behavior of devices. The past behavior or history of a device is usually referred to as contacts that the device had in the past. Whatever may be the metric of history, most of these routing protocols work on the realistic premise that node mobility is not truly random. In contrast, there are several oracles based methods where such oracles assist these methods to gain access to information that is unrealistic in the real world. Although, such oracles are unrealistic, they can help to understand the nature and behavior of underlying networks. In this paper, we have analyzed the gap between these two extremes. We have performed max-flow computations on three different opportunistic networks and then compared the results by performing max-flow computations on history generated by the respective networks. We have found that the correctness of the history based prediction of history is dependent on the dense nature of the underlying network. Moreover, the history based prediction can deliver correct paths but cannot guarantee their absolute reliability.展开更多
文摘Epidemic routing (Flooding) is considered as a simple routing protocol for opportunistic networks where the participants attempt to transmit whatever information they have to everyone who does not already have that information. However, it is plagued with disadvantages of resource scarcity as it exerts stress on available bandwidth as well as storage capacity of the devices in the network. Cognitive radio (CR) is one of the emerging technologies that can improve the bandwidth utilization by smart allocation of spectrum radio bands. Ideally speaking, a spectrum-aware cognitive radio is able to sense the local spectrum usage and adapt its own radio parameters accordingly. In this study, we have performed experiments to analyze the gains achieved by flooding protocol using cognitive radios of varying capabilities in opportunistic networks. We have performed experiments on three opportunistic networks obtained from real-life traces from different environments and presented results showing variance in delivery efficiency as well as cost incurred on those scenarios. Our results show that performance of flooding can be significantly improved using CRs in bandwidth-scarce environments;however, the improvement is not uniform with the increase in a number of available bands.
文摘Most of the existing opportunistic network routing protocols are based on some type of utility function that is directly or indirectly dependent on the past behavior of devices. The past behavior or history of a device is usually referred to as contacts that the device had in the past. Whatever may be the metric of history, most of these routing protocols work on the realistic premise that node mobility is not truly random. In contrast, there are several oracles based methods where such oracles assist these methods to gain access to information that is unrealistic in the real world. Although, such oracles are unrealistic, they can help to understand the nature and behavior of underlying networks. In this paper, we have analyzed the gap between these two extremes. We have performed max-flow computations on three different opportunistic networks and then compared the results by performing max-flow computations on history generated by the respective networks. We have found that the correctness of the history based prediction of history is dependent on the dense nature of the underlying network. Moreover, the history based prediction can deliver correct paths but cannot guarantee their absolute reliability.
