Spring 2005UCSC CMPE2571 CMPE 257: Wireless Networking SET 2: Models, Limits, Architectures, and Logic in Wireless Ad Hoc Networks

Spring 2005UCSC CMPE2572 Conferences and Journals n MONET, WINET, IEEE JSAC n IEEE Trans Mobile Computing n IEEE Trans Wireless Comm. n ACM Mobicom, ACM Mobihoc n ACM Sensys, ACM mobisys n IEEE SECON, IEEE MASS, IEEE ICNP n IEEE Infocom, IEEE WCNC, IEEE Globecom

Spring 2005UCSC CMPE2573 Emergence of Sensor and Ad Hoc Networks technology applications sensor and ad hoc networks packet radio

Spring 2005UCSC CMPE2574 Technology Push n CMOS: Far smaller chips p Small and inexpensive processing and storage n Micro sensors p Ability to sense everything, everywhere, all the time (e.g., motion, light, vibration, pressure, humidity, …, even IDs) n Wireless spectrum: availability of large amounts of unlicensed spectrum p Always-on connectivity n Radios: UWB, software radios, beam-forming, successive interference cancellation p Better ways to use available spectrum

Spring 2005UCSC CMPE2575 Technology Push (2) n Batteries and low-power chip and architecture designs p Long-term unattended operation n Hardware and software (e.g., peer-to-peer, caching, multi-modal UI) p Ability to make good trade-offs for processing, comm., energy use, application effectiveness, and interaction with the world n Robots p Ability to integrate robots and routers (“robo-router”) to augment the usefulness and capacity of wireless networks (e.g., instruct a robo-router to move to a location to collect data, reconnect a network, or improve the network throughput)

Spring 2005UCSC CMPE2576 Application Push: Netcentricity Computing (networking, processing and storage) is everywhere and invisible n Long-lived applications n Applications in highly disruptive environments (e.g., in the battlefield, monitoring of hazardous phenomena) n Applications without end-to-end connectivity n Real-time computing while interfacing with the real world n Human-to-content interaction

Spring 2005UCSC CMPE2577 H2 Example MANET: R i d f g R What happens in a typical MANET protocol stack? k C1 b c a e j m C2 h p H1

Spring 2005UCSC CMPE2578 What’s Wrong with Ad Hoc Nets? n Network control is based on algorithms designed for graphs with point-to-point links in which interference is confined to each link.

Spring 2005UCSC CMPE2579 Radio Channel Propagation Effects n Diffraction n Reflection n Scattering n Time spread n Time-varying

Spring 2005UCSC CMPE25710 Signal Strength at The Receiving Antenna(s) S(dB) Distance ReceiverSensitivity Small-scale fading shadowing Path loss

Spring 2005UCSC CMPE25711 Interference Is Network-Wide! n No centralized control is feasible n “Known” problems: p “Hidden terminal” p “Exposed terminal” p Scheduling n Topology is not a “Boolean function”: p Quality of links depends on activity of other nodes p RF propagation effects p Thermal/background noise

Spring 2005UCSC CMPE25712 What’s Wrong with Ad Hoc Nets? n Network architecture is based on the Internet architecture. p Ad hoc network is viewed either as a subnet or a “leaf” component of the Internet. p Destinations in routing tables are hosts or groups of hosts (nets).

Spring 2005UCSC CMPE25713 The Beginnings of Protocol Layering HOST IMP application n Routing within ARPANET is transparent to hosts attaching to the ARPANET n The actual “customers of ARPANET” are the hosts! n People and processes are an after thought. A “remote backbone”

Spring 2005UCSC CMPE25714 IP Internet today n A single path to each destination. n Topology is a given; link costs are static; end-to-end connectivity exists. n No control over what traffic is allowed on a given link (no usage policies) n Can’t select path with custom performance characteristics p All traffic must use resource rich path R R R R R R R R R

Spring 2005UCSC CMPE25715 IP Internet today R R R R R R R R R n Still a “remote” backbone connecting hosts! n Host processing remains far removed from router processing (how information is distributed and how resources are shared). n Usage policies must be implemented outside the routing system

Spring 2005UCSC CMPE25716 Disruption-Tolerant Networks? End-to-end connectivity need not exist! z z Very short range Remember: In the Internet model, topology is a given; link costs are static; end-to-end connectivity exists.

Spring 2005UCSC CMPE25717 Disruption-Tolerant Networks? z Consider routes as functions of space and time; exploit longer-term storage

Spring 2005UCSC CMPE25718 What’s Wrong with Ad Hoc Nets? n No good handle on self- configuring networks. Many proposals on “sufficient” conditions to ensure loop freedom, but without ensuring that the protocol signaling always ensures that such conditions are satisfied!

Spring 2005UCSC CMPE25719 Current Routing in MANETs n Pro-active routing protocols p OLSR, DSDV, and STAR. n On-demand routing protocols p Source routed data packets r e.g., DSR r Not good in very large nets (source route is brittle) p Use routing invariants to perform hop-by-hop loop-free routing (e.g., sequence numbers) r Typical case: AODV uses destination-based sequence numbers. No loop can exist because nodes can only trust higher sequence number! r Has the IETF really covered all the bases?

Spring 2005UCSC CMPE25720 Routing Using Destination Sequence Numbers n Ad-hoc On-demand Distance Vector Protocol (AODV). p Loop-freedom by ordering non-decreasing destination sequence numbers towards a destination. p Performance suffers due to nodes requiring sequence number ‘resets’ from the destination on link failures. n Termination in the presence of state loss, and node failures cannot be guaranteed.

Spring 2005UCSC CMPE25721 Fixed Spectrum Assignment R i d f e g c b R C1 Poor connectivity j m k h C2 a p

Spring 2005UCSC CMPE25722 Fixed Spectrum Assignment R i d f g R Too much interference: Nodes are forced to use parts of spectrum that are accessed by too many nodes. k C1 b c a e j m C2 h p

Spring 2005UCSC CMPE25723 Goal: Good Connectivity and Controlled Interference R i d f e g c R How should nodes elect which links to use with peers? Should decisions be “cluster” or “node” based, local or network-wide? What signaling should be applied? k C2 a p h C1 b m j

Spring 2005UCSC CMPE25724 Good Connectivity and Controlled Interference: How should nodes monitor spectrum? What is the impact of physical-layer parameters, including node location? MAC --> MASC (Medium Access and Selection Control) R i d f e g c R k C2 a p h C1 b m j

Spring 2005UCSC CMPE25725 What’s Wrong with Ad Hoc Nets? n No real clue on how users and protocol stack should use available resources efficiently. p Example, what if we have many links between the same two nodes?

Spring 2005UCSC CMPE25726 Policy-Based Routing R R Spectrum agility means far richer connectivity. We have a very different type of ad hoc nets: Any pair of nodes can be connected by multiple links. h a b e d C2 f g c p m i j k C1 wired or optical

Spring 2005UCSC CMPE25727 Policy-Based Routing At certain locations, nodes may not be allowed to use portions of the spectrum, or portions of the spectrum may suffer too much interference. R R h a b e d C2 f g c p m i j k C1 wired or optical

Spring 2005UCSC CMPE25728 Policy-Based Routing To be effective, routing in spectrum agile networks must be done with QoS, admin., and BW-use constraints Using location information is very important! R R h a b e d C2 f g c p m i j k C1 wired or optical

Spring 2005UCSC CMPE25729 Image from sensor command center Not All Nodes and Traffic Are Created Equal! Most communication is multipoint and for particular purposes

Spring 2005UCSC CMPE25730 How can we reduce interference subject to multiple constraints (spectrum available, power consumption, e-t-e delays, bandwidth requirements…)? Exploit diversity (user, space, time, code, freq), location information and cross-layer optimization S D Conventional close straight line path P-B Routing and Scalability of Networks Path of least interference and least resistance subject to constraints

Spring 2005UCSC CMPE25731 What’s Wrong with Ad Hoc Nets? n Usage policies? n Security? p Who do I have to trust to establish an ad hoc guest wireless group in a host infrastructure? p Can I exploit available resources to enhance security? n Who plays system administrator for the embedded Internet?

Spring 2005UCSC CMPE25732 Wireless Networks Are Very Different than Wireline Netwoks MAC and etiquettes establish links; need multicast group affiliations and routes to destinations of flows for better scheduling of spectrum routing needs links for transmission of control packets; packet forwarding needs links for transmission of data packets topology control determines nodes & links that can be used for certain functions; needs links for interference- free transmission of control packets, and dissemination of neighborhood data S T R Scalable & Efficient Network Control Signaling to support functions should not be redundant

Spring 2005UCSC CMPE25733 Spectrum Agile Networking S T R Scalable & Efficient Network Control constraints CONSTRAINTS: Spectrum: Spectrum allocation rules Traffic: Traffic engineering and quality of service Security and privacy would fall here Nodes: characteristics and state of nodes in the network e.g., power and storage constraints

Spring 2005UCSC CMPE25734 Role of Limits?

Spring 2005UCSC CMPE25735 Recent Limits for Ad Hoc Networks n Definition: A source-destination throughput of Λ(n) bits/sec is feasible if every source node can send information at a rate of Λ(n) bits/sec to its destination for n total nodes in the network. n Gupta and Kumar [2000] ( for static networks ) n Grossglauser and Tse [2001] (Multiuser diversity: One-copy two phase packet relay to nearest neighbor strategy for mobile networks)

Spring 2005UCSC CMPE25736 A Different Model (SECON 04 paper) n total users r0r0 Only one relay (the nearest) looking for destination Single-copy forward r0r0 n total users r0r0 First relay reaching destination (and not necessarily the nearest) delivers the packet (More than one relay looking for destination) Multi-copy forward r0r0 Uniform Mobility Model steady state distribution of nodes is uniform.

Spring 2005UCSC CMPE25737 i p j k Phase 1 d(i) Handshake (check SN) Phase 2 Enforcing One-copy Delivery n total users r0r0 r0r0 Time-to-Live threshold (TTL) forces packets in nodes p and k to be dropped.

Spring 2005UCSC CMPE25738 Results in SECON 04 Paper  Computes the interference effect and showed that  Presents an approximated formula for throughput as a function of network parameters  Computes a delay relationship between single-copy and multi-copy relay strategy n A multi-copy one-time relay strategy that attains the Θ(1) throughput but provides bounded delay for finite number of nodes n.

Spring 2005UCSC CMPE25739 Role of Limits n We need to understand fundamental performance limits for any protocol stack of the ad hoc networks we need.  Performance limits are meaningful after we have established what an ad hoc network should be.  Hence, limits are meaningful only within an architectural context.  This brings us back to the prior slides! u Examples: End-to-end connectivity is assumed for information exchange, and source-destination pairs compete with one another

Spring 2005UCSC CMPE25740 Role of Limits (Cont.) n Do we need end-to-end connectivity all the time and can (should) we even try to enforce it? p What is the actual lifetime of an average link in the battlefield? n What is the impact of locality of reference and mirroring of content near its demand points? n Why should we assume that source- destination pairs compete with one another? p What about SIC and other techniques?

Spring 2005UCSC CMPE25741 Role of Limits (Conc.) n Why shouldn’t we view storage as part of the communication bandwidth available? (turn store and forward into store-carry-forward) p Early examples: Single and multi-copy relay schemes following Grossglauser and Tse’s work n If routes are plans in time and space, what does it mean to be “connected”? n What is the capacity of a “disconnected” network?

Spring 2005UCSC CMPE25742 Modeling The Impact of Physical Layer?

Spring 2005UCSC CMPE25743 Role of Interactions in The Modeling of Ad Hoc Networks n Need to model specific protocol stacks to predict performance. n Must include physical layer aspects directly into the behavior of MAC protocols (and protocol stack) n Must consider interdependencies among nodes given by radio-based topology n Per-node performance n Model must be scalable (faster than simulation)

Spring 2005UCSC CMPE25744 Modeling: Previous Work n Single-hop or “weak interactions” approach n Scheduling rates modeled as independent Poisson processes n Packet lengths: p Exponentially distributed p Independent at each transmission attempt: r back-off schemes ignored! n Instantaneous acknowledgments n Error-free links n Assumptions on spatial distributions (e.g., Poisson) n Result: Heavy reliance on simulations

Spring 2005UCSC CMPE25745 Modeling Goal: Reflect Interactions between PHY and MAC Layers n Focus on the essentials of PHY and MAC layers: p PHY: to ensure that frames are received correctly p MAC: scheduling discipline to access the channel n PHY/MAC dynamics tightly connected n PHY/MAC interactions depend on connectivity among the nodes: r Network topology is key! n Model each layer’s functionality probabilistically: p PHY: probability of successful frame reception p MAC: transmission probability (scheduling rate)

Spring 2005UCSC CMPE25746 “Generic” Modeling Approach n PHY: p The probability of successful reception of a data packet and its acknowledgment, based on effect from all transmissions (which depend on scheduling by the MAC) and PHY parameters n MAC: p Scheduling rates based on feedback from the PHY regarding the success of transmissions n Topology: p Consider the effect of all nodes based on where they are and their transmissions p Simplify the problem taking advantage that MAC protocol will tend not to schedule transmissions when feedback from the PHY indicates unsuccessful transmissions

Spring 2005UCSC CMPE25747 Impact of Physical Layer n Consider the effect of network-wide interference n Signal-to-interference-plus-noise density ratio: where:

Spring 2005UCSC CMPE25748 Impact of Physical Layer Assume: n Successful frame reception probability  Let C i r denote a set of potential interferers:  Note that scheduling rates (taus) are given by the MAC layer!

Spring 2005UCSC CMPE25749 Impact of MAC Layer n Consider a reliable delivery service n MAC as a stochastic dynamic system: p Feedback: successful transmission probabilities p Output: scheduling rates n Steady-state operation (under saturation): n In reality, MAC’s operation is a time-varying system, and scheduling rates are also functions of packets in buffers.

Spring 2005UCSC CMPE25750 Impact of Topology: Linearization n First-order approximation of, with (because MAC will tend not to schedule transmissions when transmissions are not successful): n If n Keep term with the highest SINR:

Spring 2005UCSC CMPE25751 Linear System n Linear system: n Transmission prob. vector:

Spring 2005UCSC CMPE25752 Application: Modeling IEEE DCF in Multihop Ad Hoc Networks n M. Carvalho and J. J. Garcia-Luna-Aceves, “Delay Analysis of IEEE in Single-Hop Networks,” Proc. ICNP, Atlanta, p Node’s service time as a function of channel state probabilities p Model extension: finite back-off operation n G. Bianchi, “Performance Analysis of the IEEE Distributed Coordination Function,” IEEE JSAC, p Functional form (single-hop, ideal channel conditions)

Spring 2005UCSC CMPE25753 Model Validation: Simulation Setup n Qualnet simulator (v3.5) n Radio Channel Model: “Two-ray” n Standard IEEE DCF parameters n IEEE (PHY): p Direct sequence spread spectrum (DSSS) p DBPSK at 1Mbps p Radio range: 200 m p Carrier sensing range: 400 m p Packet reception model: BER n Independent bit errors per frame n Area: 1000 x 1000 m n Nodes randomly placed in the terrain (but connected) n Fixed packet sizes: 1500 bytes n 5 min. data traffic n 50 trials corresponding to different initial transmission times

Spring 2005UCSC CMPE25754 Model Validation: Per-node Throughput Scenario with 100 nodes

Spring 2005UCSC CMPE25755 Prediction Error Histogram over 10 random topologies (100 nodes) Sample topologies Not wonderful, but a good start!

Spring 2005UCSC CMPE25756 Complementary of Simulation Effort n Analytical model is much faster: p Simulation setup: r Platform: Sun blade 100 SunOS 5.8 r 50 seeds r 100 nodes r 5-min data traffic p Total time: hours p Analytical model: 0.44 seconds in Matlab 6.0 p Analytical model is 10 5 faster than simulations! n Scalable simulations can address entire protocol stack and complex scenarios!

Spring 2005UCSC CMPE25757 Role of logic?

Spring 2005UCSC CMPE25758 Logic in Ad Hoc Networks n The logic is in the signaling used to control the networks. n Goal: Self-organizing and scalable ad hoc networks n Protocol layers operate in isolation (e.g., routing, MAC scheduling and topology control are mutually independent) n Too many assumptions are being made p Single channel, all nodes are equal, etc. n Many proposals on “sufficient” conditions to ensure loop freedom exist, but without ensuring that the protocol signaling always ensures that such conditions are always satisfied! n Too much reliance on global variables (e.g., hold down timers after reboot)

Spring 2005UCSC CMPE25759 Example: Routing in MANETs n Pro-active routing protocols p Examples, OLSR, DSDV, and STAR. p Too much signaling since not all nodes need to talk to all other nodes with same likelihood. n On-demand routing protocols p Source routed data packets r e.g., DSR r Not good in very large nets (source route is brittle) p Use routing invariants to perform hop-by-hop loop-free routing (e.g., sequence numbers) r Typical case: AODV uses destination-based sequence numbers. Hope: No loop can exist because nodes can only trust higher sequence number!

Spring 2005UCSC CMPE25760 Routing Using Destination Sequence Numbers n Example: Ad-hoc On-demand Distance Vector Protocol (AODV). p Loop-freedom by ordering non-decreasing destination sequence numbers towards a destination. p Performance suffers due to nodes requiring sequence number ‘resets’ from the destination on link failures. n Termination in the presence of state loss, and node failures cannot be guaranteed without a global parameter. p Recent example: “Wait until none of the network nodes can possibly use node is question in their paths to a destination.” n How long is it safe to wait after state loss to ensure no counting-to-infinity?

Spring 2005UCSC CMPE25761 Logic in Ad Hoc Networks n Need to consider network architecture and fundamental limits! p Spectrum agility for scaling p Role of store-carry-forward and routes as plans in space and time p Modular signaling that works well for tiny and very large networks, none or multiple policies, and without anyone having to choose parameter values. p Cross-layer interaction

Spring 2005UCSC CMPE25762 In summary… ARCHITECTURES LIMITS ANALYTICAL MODELS & SIM LOGIC: Self-Organizing, scalable