Abstract
We consider the problem of routing packets with end-to-end hard deadlines in multihop communication networks. This is a challenging problem due to the complex spatial–temporal correlation among flows with different deadlines. To tackle this problem, we introduce the concepts of virtual links and virtual routes to incorporate end-to-end deadline constraints into routing and propose a novel virtual queue architecture to guide the spatial–temporal routing where the routing algorithm specifies where and when a packet should be routed. For the frame-based periodic traffic, the proposed policies can support any arrival within throughput region when the ratio between the link capacity and the packet size is sufficiently large. For the general traffic, we integrate a constrained resource-pooling heuristic into the spatial–temporal routing, which improves the delivery ratio and performs well. Our extensive simulations show that the policies outperform traditional policies such as backpressure and earliest-deadline-first (EDF) for more general traffic flows in multihop communication networks.
| Original language | English (US) |
|---|---|
| Article number | 102007 |
| Journal | Performance Evaluation |
| Volume | 135 |
| DOIs | |
| State | Published - Nov 1 2019 |
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Keywords
- End-to-end deadline
- Spatial–temporal routing
- Throughput optimality
ASJC Scopus subject areas
- Software
- Modeling and Simulation
- Hardware and Architecture
- Computer Networks and Communications
Cite this
Spatial–temporal routing for supporting end-to-end hard deadlines in multi-hop networks. / Liu, Xin; Wang, Weichang; Ying, Lei.
In: Performance Evaluation, Vol. 135, 102007, 01.11.2019.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Spatial–temporal routing for supporting end-to-end hard deadlines in multi-hop networks
AU - Liu, Xin
AU - Wang, Weichang
AU - Ying, Lei
PY - 2019/11/1
Y1 - 2019/11/1
N2 - We consider the problem of routing packets with end-to-end hard deadlines in multihop communication networks. This is a challenging problem due to the complex spatial–temporal correlation among flows with different deadlines. To tackle this problem, we introduce the concepts of virtual links and virtual routes to incorporate end-to-end deadline constraints into routing and propose a novel virtual queue architecture to guide the spatial–temporal routing where the routing algorithm specifies where and when a packet should be routed. For the frame-based periodic traffic, the proposed policies can support any arrival within throughput region when the ratio between the link capacity and the packet size is sufficiently large. For the general traffic, we integrate a constrained resource-pooling heuristic into the spatial–temporal routing, which improves the delivery ratio and performs well. Our extensive simulations show that the policies outperform traditional policies such as backpressure and earliest-deadline-first (EDF) for more general traffic flows in multihop communication networks.
AB - We consider the problem of routing packets with end-to-end hard deadlines in multihop communication networks. This is a challenging problem due to the complex spatial–temporal correlation among flows with different deadlines. To tackle this problem, we introduce the concepts of virtual links and virtual routes to incorporate end-to-end deadline constraints into routing and propose a novel virtual queue architecture to guide the spatial–temporal routing where the routing algorithm specifies where and when a packet should be routed. For the frame-based periodic traffic, the proposed policies can support any arrival within throughput region when the ratio between the link capacity and the packet size is sufficiently large. For the general traffic, we integrate a constrained resource-pooling heuristic into the spatial–temporal routing, which improves the delivery ratio and performs well. Our extensive simulations show that the policies outperform traditional policies such as backpressure and earliest-deadline-first (EDF) for more general traffic flows in multihop communication networks.
KW - End-to-end deadline
KW - Spatial–temporal routing
KW - Throughput optimality
UR - http://www.scopus.com/inward/record.url?scp=85070376328&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85070376328&partnerID=8YFLogxK
U2 - 10.1016/j.peva.2019.102007
DO - 10.1016/j.peva.2019.102007
M3 - Article
AN - SCOPUS:85070376328
VL - 135
JO - Performance Evaluation
JF - Performance Evaluation
SN - 0166-5316
M1 - 102007
ER -