On the Cost/Delay Tradeoff of Wireless Delay Tolerant Geographic Routing Argyrios Tasiopoulos MSc, student, AUEB Master Thesis presentation.

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Presentation transcript:

On the Cost/Delay Tradeoff of Wireless Delay Tolerant Geographic Routing Argyrios Tasiopoulos MSc, student, AUEB Master Thesis presentation

Introduction Many networks are characterized by: –Intermittent Connectivity. –Long or variable delays. In both cases traditional TCP/IP protocols fail. Delay Tolerant Networking addresses these issues. 4 to 20 minutes Master Thesis presentation

Delay Tolerant Networks (DTNs) In Delay-Tolerant Networks each node can hold packets indefinitely in a persistent buffer. The previous problems are addressed by store-and-forward message switching.

Mobile Delay Tolerant Networks In mobile DTNs, nodes can carry a packet physically in their buffer. Therefore, we actually have store-carry- and-forward packet switching. 4 Master Thesis presentation

DTNs Protocol Design In DTNs we have an extra degree of freedom regarding the delay in data delivery. We can trade off delay in order to improve other metrics. Our case of study concerning the improvement of aggregate transmission cost. –We care about the behavior of aggregate transmission cost of a packets given a delivery delay. 5WoWMoM San Francisco 2012

Aggregate Transmission Cost What we mean in this work when we talk about aggregate transmission cost? –The cost of interference (typically proportional to transmission area), and/or –the energy consumption of a transmission (typically fixed). 6 Master Thesis presentation

Coming next Part A: Optimal Cost/Delay Tradeoff Formulation Part B: Cost/Delay Tradeoffs in Geographic Routing Part C: Simulation Environments and Results 7 Master Thesis presentation

Part A: Optimal Cost/Delay Tradeoff Formulation. 8 Master Thesis presentation

Optimal Cost/Delay Tradeoff We take the typical approach of evolving graphs (Ferreira 2004). We divide the time into discrete time intervals, called epochs. We make the assumptions that during each epoch: –the network topology remains fixed, hence creates a network replica for the specific epoch, and –all packet transmissions can take place. 9 Master Thesis presentation

Cost/Delay Evolving Graph We define as Cost/Delay Evolving Graph (C/DEG) the graph comprised by: –consecutive replicas, –link arcs, which connect nodes along the same replica, and –storage arcs, which connect the same nodes along consecutive replicas. 10 Master Thesis presentation

Punctual vs. Optimal Cost/Delay Curve Given a packet source we can execute any one-to-many shortest path algorithm. We define the Punctual Cost/Delay Curve (PC/DC), as the minimum-cost journey of exactly t epochs, between two nodes. We define the Optimal Cost/Delay Curve (OC/DC), as the minimum-cost journey of all journeys with the maximum duration of t epochs. WoWMoM San Francisco

Punctual Cost/Delay Curve Example WoWMoM San Francisco

Punctual vs. Optimal Cost/Delay Curve Example 13 Master Thesis presentation

Part B: Cost/Delay Tradeoffs in Geographic Routing. 14 Master Thesis presentation

Geographic routing In geographic routing a source sends a message to the geographic location of the destination. 15 R Master Thesis presentation

Geographic routing Then, the packet route from source to destination is calculated “on the fly”. 16 Master Thesis presentation Complete network topology

Protocol family Each node which executes a protocol of this family: –Applies a Neighbor Evaluation Rule (NER) to its immediate neighbor nodes, which returns the best of them. –Calculates the minimum-cost path to the best neighbor. –Forwards the packet to the next hop node along the minimum-cost path. 17 Master Thesis presentation

Protocol Family Example 18 Execute NERFind the best Calculate shortest-cost path Forward the packet to the next hop node Master Thesis presentation

Protocol Family Variations Next we define 5 member of this protocol family. All rules differ on NER. For the rest of this presentation: –node A is the packet holder which performs the NER, –node B is a candidate neighbor of A, and –node D the packet destination. 19 Master Thesis presentation

Motion Vector (MoVe) (LeBrun et al.,2005) MoVe NER: Select as best the node with the current or future closest distance from the destination. Minimizes |ZD| 20 Master Thesis presentation

AeroRP (Peters et al., 2011) AeroRP NER: Selects as best the node with the biggest relative velocity towards destination Maximizes v RB 21 Master Thesis presentation

Minimum Cost-per-Progress (MCpPR) MCpPR NER minimizes the ratio: 22 Master Thesis presentation

Balance Ratio Rule (BRR) Our first novel protocol minimizes the ratio: We define α as the conversion coefficient. –Which strikes a balanced between cost and delay by trying to keep them both low. 23 Master Thesis presentation

Composite Rule (CR) MCpPR rule tries to maximize the immediate transmission gains. BRR tries to maximize the benefits of the physical transportation of store-carry-and- forward packet switching. Hence, we define Composite Rule (CR) as the best of two worlds which minimizes simultaneously the ratios of MCpPR and BRR : 24 Master Thesis presentation

Achievable Cost/Delay Curve (AC/DC) We define the AC/DC as the curve that give for each epoch, the minimum aggregate transmission cost that a protocol can achieve for a pair of nodes. If the protocol has tunable parameters concerning the tradeoff, an achievable cost/delay curve (AC/DC) is calculated in a similar way to OC/DC, over the complete range of results of these parameters. 25 Master Thesis presentation

Achievable Cost/Delay Tradeoff Example 26 Master Thesis presentation

Part C: Simulation Environments and Results. 27 Master Thesis presentation

Performance Evaluation Settings We evaluate our protocols in the 3 following settings: –empty space setting, –home region setting, and –urban setting. 28 Master Thesis presentation

Simulation parameters The common tunable parameter for all these protocols is the restricted radius R’ which determines the maximum transmission hop length. CR and BRR have the extra tunable parameter α. Standard case: The nodes move with random velocities and we have a quadratic aggregate transmission cost function (equal to d 2 where d the transmission distance). 29 Master Thesis presentation

Empty Space Setting 30 Master Thesis presentation

Empty Space Setting – Fixed velocities and cost function 31 Master Thesis presentation

Home Region Setting 32 Master Thesis presentation

Urban Setting Master Thesis presentation

Urban Setting-Fixed velocities 34 Master Thesis presentation

Conclusions Our immediate contributions: –The formulation of optimal tradeoff between the packet delivery delay and the aggregate transmission cost existing in all DTNs. –The study of this tradeoff in the context of geographic routing –Our two novel rules with results close to the optimal. Our most important contribution: –We set the agenda for a systematic evaluation of cost/delay tradeoffs in a variety of DTNs settings. 35 Master Thesis presentation

Thank you