Yongjian Yang

A Knapsack-based buffer management strategy for delay-tolerant networks

Abstract In delay-tolerant networks, the dramatic change of topology and the frequent interruption of connections make it difficult to forward the message to destination. Routing protocols in DTNs seek to improve the delivery ratio through increasing the number of message copies. However, the redundant message copies easily cause the occurrence of buffer’s overflowing. In this paper, in order to maximize the utilization of network resources, especially when the bandwidth is limited and the message sizes are different, we present a theoretical framework called the Knapsack-based Message Scheduling and Drop strategy in Theory (KMSDT) based on Epidemic routing protocol. KMSDT sorts the messages in the buffer according to the per-unit utility and, if buffer overflows, decides which message to drop based on the solution to the knapsack problem. Furthermore, a practical framework called the Knapsack-based Message Scheduling and Drop strategy in Practice (KMSDP) is also developed. Rather than collecting the global statistics as done in KMSDT, KMSDP estimates all the parameters through the locally-collected statistics. Simulations based on both synthetic and real mobility traces are done in ONE. Results show that, without affecting the average delay and overhead ratio, KMSDP and KMSDT achieve better delivery ratio than other congestion control strategies.

A Knapsack-Based Message Scheduling and Drop Strategy for Delay-Tolerant Networks

Because of the dramatic changes in topology and frequently interrupted connections between nodes, messages in delay-tolerant networks are forwarded in the store-carry-forward approach. Routing methods in such an environment tend to increase the number of messages to improve the delivery ratio. However, excessive message copies lead to buffer overflows because of limited storage space. Therefore, an efficient message-scheduling and drop strategy is vital to maximizing network resources, especially when bandwidth is limited and message sizes differ. We developed a theoretical framework called the knapsack-based message scheduling and drop strategy in theory (KMSDT) based on epidemic message dissemination. To improve the delivery ratio, this strategy sorts message copies by utility per unit and, if buffer overflows occur, it decides which messages to drop based on the solution to the knapsack problem. Furthermore, we developed a practical framework called the knapsack-based message scheduling and drop strategy in practice (KMSDP). Rather than collecting global statistics as done in the KMSDT, KMSDP estimates all parameters by using locally collected statistics. Simulations based on synthetic trace are done in ONE. Results show that, without affecting the average delay or overhead ratio, KMSDP and KMSDT achieve a better delivery ratio than other congestion-control strategies.

Phone-to-Phone Communication Utilizing WiFi Hotspot in Energy-Constrained Pocket Switched Networks

In pocket switched networks (PSNs), devices carried by humans form a network environment, which utilizes both human mobility and occasional connectivity to deliver messages among mobile devices. Mobile phones are widely used in our daily lives. Therefore, the PSN composed of human-carried mobile phones will soon become an ubiquitous network environment. In this paper, we propose a communication strategy that applies the WiFi hotspot mode of a mobile phone in the PSN to realize the device-to-device communications. However, due to the lack of energy supply, a phone in hotspot mode could rapidly consume energy and shorten its battery lifetime significantly. To maximize the message dissemination scope within the limited energy constraint of each phone in PSNs, an Energy-efficient Phone-to-phone Communication method based on WiFi Hotspot (EPCWH) is presented to schedule the phones switching between hotspot mode and client mode. Simulations based on the synthetic random-waypoint mobility pattern and real traces are conducted in an opportunistic network environment; the results show that EPCWH achieves the best performance in terms of message dissemination and energy consumption among different switching strategies.

Dynamic beaconing control in energy-constrained Delay Tolerant Networks

Due to the uncertainty of network topology and intermittent connectivity among nodes in Delay Tolerant Networks (DTNs), beaconing is used to detect probabilistic contacts. However, it causes the following new problem: beaconing frequency not only influences the probability of message transmission, but also affects the consumption rate of energy. Thus, putting forward a beaconing control strategy in energy-constrained DTNs becomes the key point. In this paper, we propose an efficient and dynamic beaconing control method DBCEC in energy-constrained DTNs based on the time-continuous Markov Model. A linear decline strategy (i.e. DBCEC-L) and exponential decay strategy (i.e. DBCEC-E) are respectively applied to control the beaconing frequency. Simulations based on the synthetic mobility model and real mobility traces are conducted in ONE, and results show that DBCEC-E achieves a better delivery rate without influencing average delay and the overhead ratio, compared with other beaconing control strategies.

A Buffer Scheduling Method Based on Message Priority in Delay Tolerant Networks

Routing protocols in delay tolerant networks usually utilize multiple message copies to guarantee the message delivery, in order to overcome unpredictable node mobility and easily-interrupted connections. A store-carry-and-forward paradigm was also proposed to further improve the message delivery. However, excessive message copies lead to the shortage of buffer and bandwidth. The spray and wait routing protocol has been proposed to reduce the network overload caused by the buffer and transmission of unrestricted message copies. However, when a node’s buffer is quite constrained, there still exist congestion problems. In this paper, we propose a message scheduling and drop strategy on spray and wait routing protocol (SDSRP). To improve the delivery ratio, first of all, SDSRP calculates the priority of each message by evaluating the impact of both replicating and dropping a message copy on delivery ratio. Subsequently, scheduling and drop decisions are made according to the priority. In order to further increase delivery ratio, we propose an improved message scheduling and drop strategy on spray and wait routing protocol (ISDSRP) through enhancing the accuracy of estimating parameters. Finally, we conduct extensive simulations based on synthetic and real traces in ONE. The results show that compared with other buffer management strategies, ISDSRP and SDSRP achieve higher delivery ratio, similar average hopcounts, and lower overhead ratio.

A Buffer Management Strategy on Spray and Wait Routing Protocol in DTNs

Due to unpredictable node mobility and the easily-interrupted connections, routing protocols in DTNs commonly utilize multiple message copies to improve the delivery ratio. A store-carry-and-forward paradigm is also designed to assist routing messages. However, excessive message copies lead to rapid consumption of the limited storage and bandwidth. The spray and Wait routing protocol has been proposed to reduce the network overload caused by the storage and transmission of unrestricted message copies. However, there still exist congestion problems when a nodes buffer is quite constrained. In this paper, we propose a message Scheduling and Drop Strategy on spray and wait Routing Protocol (SDSRP). To improve the delivery ratio, first of all, SDSRP calculates the priority of each message by evaluating the impact of both replicating and dropping a message copy on delivery ratio. Subsequently, scheduling and drop decisions are made according to the priority. Finally, we conduct extensive simulations based on synthetic and real traces in ONE. The results show that, compared with other buffer management strategies, SDSRP achieves higher delivery ratio, similar average hop counts, and lower overhead ratio.

An Efficient Prediction-Based User Recruitment for Mobile Crowdsensing

Mobile crowdsensing is a new paradigm in which a group of mobile users exploit their smart devices to cooperatively perform a large-scale sensing job. One of the users’ main concerns is the cost of data uploading, which affects their willingness to participate in a crowdsensing task. In this paper, we propose an efficient Prediction-based User Recruitment for mobile crowdsEnsing (PURE), which separates the users into two groups corresponding to different price plans: Pay as you go (PAYG) and Pay monthly (PAYM). By regarding the PAYM users as destinations, the minimizing cost problem goes to recruiting the users that have the largest contact probability with a destination. We first propose a semi-Markov model to determine the probability distribution of user arrival time at points of interest (PoIs) and then get the inter-user contact probability. Next, an efficient prediction-based user-recruitment strategy for mobile crowdsensing is proposed to minimize the data uploading cost. We then propose PURE-DF by extending PURE to a case in which we address the tradeoff between the delivery ratio of sensing data and the recruiter number according to Delegation Forwarding. We conduct extensive simulations based on three widely-used real-world traces: roma/taxi, epfl, and geolife. The results show that, compared with other recruitment strategies, PURE achieves a lower recruitment payment and PURE-DF achieves the highest delivery efficiency.

Energy Efficient Beaconing Control Strategy Based on Time-Continuous Markov Model in DTNs

In delay-tolerant networks (DTNs), unpredictable mobility leads to the uncertainty of network topology, and it is hard to maintain an end-to-end connection from the source to the destination. To realize the forwarding of the messages, beaconing is used to detect the contact probabilities. However, beaconing frequency not only influences the detection probability of the available communications but is concerned with the energy consumption rate as well. The higher the beaconing frequency is, the faster the energy is consumed. The energy consumption leads to the reduction of the network survival time, due to the lack of energy supply. In contrast, the lower the beaconing frequency is, the less frequently available communications are detected, which also leads to a decrease in delivery rate. Therefore, it is meaningful to find out the most suitable beaconing frequency in specific DTNs. In this paper, we propose an energy efficient dynamic beaconing control strategy in energy-constrained DTNs (DBCEC) based on the time-continuous Markov model. Six different dynamic function forms are, respectively, used to control the beaconing frequency. Simulations based on the synthetic mobility pattern and real mobility traces are conducted in the Opportunistic Network Environment (ONE), and the results show that DBCEC-E achieves a better delivery rate without affecting the average delay and the overhead ratio, compared with other beaconing control strategies.

A Comprehensive Forwarding Strategy in DTNs: Theory and Practice

Delay tolerant networks (DTNs) are featured by unpredictable mobility patterns and easily interrupted connections. Forwarding strategy has always been the research focus in DTNs, in order to improve a delivery ratio. An enormous amount of research works pay attention to solving the following two problems: whether to forward and how to forward. Therefore, forwarding metrics and forwarding strategies both play important roles in DTNs. In this paper, we consider a generalized random-waypoint model with heterogeneous nodes; the nodes speed is regarded as the forwarding metric, which includes both short-term and long-term speed. Subsequently, we propose a theoretical, multicopy delegation forwarding based on short-term and long-term speed in DTNs (DFSL-T), which first determines a comprehensive mapping from short-term speed and long-term speed to the actual forwarding metric. Then, according to the forwarding metric and delegation forwarding strategy, DFSL-T utilizes some efficient nodes with higher forwarding metrics to assist in delivering messages, in order to improve the delivery ratio while reducing the forwarding cost. However, DFSL-T assumes that each node could achieve the average speeds of the others, which is impractical. In order to overcome this problem, we further propose a practical strategy (DFSL-P) through exchanging and evaluating the average speeds of each other. Finally, we conduct simulations based on the synthetic mobility pattern and real trace. The results show that compared with other multicopy forwarding strategies, DFSL-T and DFSL-P achieve higher forwarding efficiency, which is the result of delivery ratio divided by forwarding cost.

A Multi-Copy Delegation Forwarding Based on Short-Term and Long-Term Speed in DTNs

Delay Tolerant Networks (DTNs) are featured by unpredictable mobility patterns and easily-interrupted connections. Forwarding strategy has always been the research focus, in order to improve the delivery ratio. An enormous amount of researches pay attention to solving the following two problems: whether to forward, and how to forward. Therefore, forwarding metrics and forwarding strategies both play important roles in DTNs. In this paper, we consider a generalized random-waypoint model with heterogeneous nodes, the nodes speed is regarded as the forwarding metric, which includes the short-term and long-term speed. Subsequently, we propose a multi-copy Delegation Forwarding based on Short-term and Long-term speed in DTNs (DFSL), which first determines a comprehensive mapping from short-term speed and long-term speed to the actual forwarding metric. Then, according to the forwarding metric and delegation forwarding strategy, DFSL utilizes some efficient nodes with higher forwarding metrics to assist in delivering messages, in order to improve the delivery ratio, while reducing the forwarding cost. Finally, we conduct simulations based on the synthetic mobility pattern and real trace. The results show that, compared with other multi-copy forwarding strategies, DFSL achieves the highest forwarding efficiency, which is defined as the result of delivery ratio divided by forwarding cost.