Utafiti huu unachunguza mifumo ya Named Data Networking (NDN) katika maeneo ya majanga ambako miundombinu ya mawasiliano ya ardhini imeharibika na ndege zisizo na rubani zinazobaki hewani katika nafasi thabiti hutumiwa kama relays za mawasiliano. Watafiti walitengeneza Regional Forwarding Strategy (RIF) ili kupunguza kusambaa kwa Interest packets kwenda maeneo ya kijiografia yasiyo ya lazima na kupunguza kutumwa tena kwa pakiti ile ile mara kwa mara na UAV jirani. Katika simulations linganishi kwenye mazingira ya ndnSIM, RIF ilionyesha kiwango cha juu zaidi cha mafanikio ya kupata pakiti, latency ndogo ya kupata data na jumla ndogo ya packet transmissions kuliko Flooding, BPF, RRDP na E-GIF. Hata hivyo, findings zinategemea controlled simulation yenye UAV positions thabiti na mawasiliano ya IEEE 802.11b, si field test halisi ya eneo la janga.

RIF inaunganisha mechanisms tatu kuu: extended packet fields zinazoonyesha kama Interest packet imefika kwenye target region, Region Location Table inayohifadhi three-dimensional coordinates za maeneo, na probabilistic suppression inayozingatia remaining energy ya nodes pamoja na idadi ya transmissions kutoka kwa neighbors. Kwa njia hii, packets husonga kupitia UAV zinazokaribia target region pekee, huku retransmission ya pakiti ile ile na relays nyingi kupita kiasi katika local neighborhood ikipunguzwa.

Kulingana na simulation graphs, Interest packet sending rate inapofika packets 8 kwa sekunde, successful packet acquisition ratio ya RIF inabaki karibu 0,84, huku Flooding ikishuka hadi karibu 0,75. Katika traffic level hiyo hiyo, average acquisition delay ya RIF ni karibu sekunde 0,40, ya Flooding karibu sekunde 0,60, na ya RRDP karibu sekunde 0,62. Values hizi zimesomwa takribani kutoka kwenye graphs; utafiti hautoi raw numerical data tables, confidence intervals au error bars.

Tatizo kuu la utafiti ni lipi?

Tatizo kuu ni kwamba traditional broadcast behavior ya NDN katika temporary UAV-assisted networks baada ya janga inaweza kuzalisha idadi kubwa ya packets zisizo za lazima. Katika NDN, mawasiliano hayalengi moja kwa moja anuani ya server fulani; yanafanywa kupitia jina la content inayotakiwa. Command center inapohitaji situation report kutoka eneo fulani la janga, hutengeneza “Interest packet”; sensor au data producer mwingine katika target region hurudisha “Data packet”.

Katika traditional flooding, Interest packet iliyopokelewa na UAV inaweza kutangazwa kwa neighbors wote wanaofaa bila kujali kama wanahusiana na target region. Watafiti wanaeleza kwamba hii huunda inefficiencies mbili tofauti:

• Ineffective forwarding: Interest packet kupelekwa kwenye geographic regions zisizo na data inayotafutwa.
• Duplicate forwarding: UAV jirani kadhaa kutuma tena copies za Interest packet ile ile.

Hali hizi mbili zinaweza kujaza wireless channel kwa packets zisizo za lazima, kuongeza probability ya collision na retransmission, kuongeza data-acquisition time na kuongeza communication burden kwa UAV zinazotumia betri.

Kwa nini utafiti ni muhimu?

Ikiwa fixed communication towers, power sources au terrestrial backbone links zimeacha kufanya kazi katika eneo la janga, UAV zinaweza kuunda temporary wireless backbone. Katika network model ya utafiti, kila UAV inabaki katika fixed position juu ya geographic region fulani, inahudumia sensors ndani ya coverage area yake na kufanya kazi kama multi-hop relay kwa maeneo mengine.

Kwa mtazamo wa Uturuki, approach hii haitegemei nchi moja au aina moja ya janga. Inaweza kuzingatiwa kwa temporary data transfer kati ya maeneo ambayo communication infrastructure imekatika kutokana na earthquake, forest fire, flood, landslide au large-area search-and-rescue operations. Hata hivyo, utafiti haukujaribu integration ya mfumo huu na regulations za Uturuki, frequency allocations, terrain conditions au real disaster-management infrastructure.

Ni pengo gani katika literature linalolengwa?

Baadhi ya previous methods husuppress copies za pakiti ile ile kwa timers lakini hazizuii packet kusonga kwenda geographic regions zisizo sahihi. Baadhi ya location-based methods hupeleka packet kuelekea target lakini hazitumii strict regional boundary, au hutuma periodic “Hello” messages ili kusasisha neighborhood information.

Main approaches zilizolinganishwa katika utafiti ni:

RIF strategy inafanyaje kazi?

1. Packet-processing module

RIF inaongeza fields mpya kwenye NDN Interest na Data packets. Interest packet inaongezewa Flag, Location na Area; Data packet inaongezewa Location na Area.

• Flag: Inaonyesha kama Interest packet imefika target region au la.
• Location: Hubeba coordinates za relay UAV inayochakata packet.
• Area: Hubeba number ya current region inayohudumiwa na UAV.

Command center inapozalisha Interest packet, Flag value inawekwa 1. Hii inaonyesha kuwa packet bado haijafika target region. Relay UAV ikigundua target-region number katika packet ni sawa na region yake, hupeleka packet kwa producers ndani ya coverage yake na kuweka Flag kuwa 0. Relay UAV nyingine ikipokea packet yenye Flag=0, huidrop badala ya kuibroadcast tena, kwa sababu packet inachukuliwa kuwa tayari imefika target region.

Katika mfano wa utafiti, command center inaomba situation report ya region ya tatu kwa jina /sitrep/area/3. Katika traditional forwarding, request hii inaweza kufika producers na relays nje ya region ya tatu. RIF inalenga kuzuia packet kusambazwa tena nje ya region baada ya kufika target region.

Katika original title ya utafiti, strategy inaitwa “Regional Interest Forwarding”, lakini katika abstract na methods section inaitwa “Regional Information Forwarding”. Maneno yote mawili yametolewa kwa abbreviation RIF. Terminological difference hii imehifadhiwa kama ilivyo katika utafiti na haijasahihishwa kimyakimya.

2. Region Location Table

Kila relay UAV ina Region Location Table (RLT). Table hii huhifadhi region numbers zinazojulikana pamoja na X, Y na Z coordinates za maeneo hayo. Table haijifunzi kupitia periodic Hello messages, bali kupitia location information inayoongezwa kwenye Interest na Data packets zinazobebwa katika network.

Uendeshaji unaweza kufupishwa hivi:

1. Command center hutuma Interest packet kwa relays jirani.
2. Relay inayopokea packet huhifadhi region na coordinate information ya previous node kwenye RLT yake.
3. Relay huandika coordinates zake na region number yake kwenye packet kisha kuituma.
4. Producer katika target region anapotengeneza Data packet, coordinates za target region zinaongezwa kwenye Data packet.
5. Data packet inapokuwa inarudi, intermediate relays hujifunza location ya target region.

Approach hii inaruhusu location information kubebwa pamoja na data traffic bila kuzalisha additional periodic control traffic. Hata hivyo, utafiti haujatathmini quantitatively inachukua muda gani kwa nodes zote kujifunza up-to-date information za regions zote, additional traffic katika initial learning period, au ni lini old RLT entries zinafutwa.

3. Forwarding kulingana na distance kwenda target

Relay UAV ikijua coordinates za target region, huhesabu distance kutoka position yake na distance kutoka previous node ilikotoka packet kwenda target. Utafiti unatumia three-dimensional Euclidean distance:

\[ dis(i,j) = \sqrt{(x_i-x_j)^2+(y_i-y_j)^2+(z_i-z_j)^2} \]

Hapa i na j zinaonyesha nodes mbili zinazolinganishwa au node moja na target region; x, y na z ni three-dimensional coordinate components. Katika simulation context, coordinates ziko katika metres na calculated distance pia inatafsiriwa kwa metres.

Ikiwa current node iko karibu na target region kuliko previous node, packet huhifadhiwa kwa forwarding. Ikiwa iko mbali zaidi, packet hudropped. Ikiwa RLT entry ya target region bado haipo, node haiwezi kutathmini direction deviation, hivyo hupeleka packet kwenye hatua inayofuata. Exception hii inazuia first requests kwenda unknown target kuzuiwa kabisa; lakini katika first requests, effect ya regional restriction inaweza kuwa ndogo zaidi.

4. Energy-aware timer

Relay inayokaribia target haitumi packet mara moja, bali huanzisha backoff timer. Relationship ya kwanza imetolewa katika utafiti kama:

\[ T = T_{\max}\left(1-\frac{E_R}{E_{\mathrm{init}}}\right) \]

T ni waiting time, T_max ni maximum allowed waiting time, E_R ni remaining energy ya node na E_init ni initial energy. Node yenye high remaining energy ina short waiting time, huku node yenye lower energy ikiwa na longer waiting time. Lengo ni UAV zenye high energy kutuma mapema na UAV ambazo energy yake imepungua kubeba forwarding load ndogo.

Baadaye utafiti unatoa second timer relationship inayojumuisha low-energy threshold:

\[ T = \begin{cases} -\log\left(\frac{E_R}{E_{\mathrm{init}}}\right), & E_R > E_{\min} \\ T_{\max}, & E_R \leq E_{\min} \end{cases} \]

E_min ni minimum energy threshold ambapo node itaingia sleep au suppression state. Ikiwa energy iko chini ya threshold hii, waiting time inawekwa kuwa T_max.

Kuna point isiyoelezwa wazi katika presentation ya formula hizi mbili. Katika first formula, dimensionless energy ratio imezidishwa kwa T_max, hivyo result ina time unit. Katika first branch ya second formula, kuna dimensionless logarithm pekee; haijaelezwa inavyobadilishwa kuwa seconds au ni scaling coefficient gani inatumika. Pia base ya logarithm na numerical values za T_max, E_min na initial energy hazijawekwa katika simulation-parameter table.

5. Probabilistic suppression kulingana na neighbor count

Wakati timer inaendelea, node husikiliza kama Interest packet ile ile imetumwa na neighbors wengine. Idadi ya different neighbors ambao wametuma packet hiyo tayari inaonyeshwa kwa N_neighbour. Transmission probability ya node inahesabiwa hivi:

\[ 0 < P = \frac{1}{N_{\mathrm{neighbour}}+1} \leq 1 \]

• Ikiwa hakuna neighbor aliyesambaza, N=0 na P=1; node hutuma packet kwa uhakika.
• Ikiwa neighbor mmoja ametuma, P=1/2.
• Ikiwa neighbors wawili wametuma, P=1/3.
• Kadiri idadi ya neighbor transmissions inavyoongezeka, probability ya kutuma additional copy inapungua.

Timer ikiisha, node hutuma packet kwa probability P na huidrop kwa probability 1−P. Lengo ni kuhifadhi connectivity katika sparse networks na kusuppress broadcast storm katika dense neighborhoods.

Simulation setup imeundwaje?

RIF ilitathminiwa kwa kutumia ndnSIM, NDN simulator inayotegemea NS-3. Wireless communication technology ilichaguliwa kuwa IEEE 802.11b na kila experiment ilidumu sekunde 300. Utafiti unasema simulations 20 zilifanywa kwa kila configuration.

Scenario ya kwanza inatathmini jinsi forwarding strategies zinavyofanya kazi wakati network load inaongezeka. Scenario ya pili inachunguza jinsi data-collection performance inavyobadilika katika network area kubwa wakati idadi ya command-center regions inaongezeka kutoka moja hadi nne.

UAV altitude ilichaguliwaje?

Katika simulation, inter-node communication distance iliwekwa metres 200, na effect ya UAV altitude kwenye ground-coverage radius ilimodelliwa separately. Graph inaonyesha ground-coverage radius ikipungua kadiri altitude inavyoongezeka, na katika altitude ya metres 170 radius ni metres 105,35. Watafiti walichagua point hii kama placement yenye low overlap kati ya neighboring coverage areas.

Hata hivyo, graph inaonyesha katika lower altitudes coverage radius ni kubwa kuliko metres 105,35. Kwa hiyo expressions “maximize coverage” na “near-maximum ground coverage” katika text hazipatani kikamilifu na curve inayoonyeshwa na graph yenyewe. Result inaonekana zaidi kama balance point kati ya coverage na overlap ya neighboring regions kuliko point yenye highest raw coverage radius; lakini explicit objective function kwa optimization hii haijatolewa.

Main findings zinaonyesha nini?

Success ratio wakati traffic density inaongezeka

Katika strategies zote, successful packet acquisition ratio ilipungua kadiri Interest packets per second zilivyoongezeka. Trend hii inaonyesha kwamba denser packet traffic inasababisha collisions na congestion zaidi katika network. RIF iliendelea kuwa na highest success ratio katika sending rates zote.

Ukisoma graph kwa makadirio, katika packet 1 kwa sekunde success ratio ya RIF ni karibu 0,97 na ya Flooding karibu 0,93. Katika packets 8 kwa sekunde, RIF inashuka hadi karibu 0,84, E-GIF 0,81, RRDP 0,78, BPF 0,77 na Flooding 0,75.

Data-acquisition delay

Kadiri sending rate inavyoongezeka, average data-acquisition delay ya methods zote inaongezeka. RIF kupunguza forwarding katika non-target regions hupunguza network load na unnecessary path lengths, na hivyo kutoa lowest delay.

Katika Interest packets 8 kwa sekunde, graph inaonyesha RIF karibu sekunde 0,40, E-GIF 0,45, BPF 0,50, Flooding 0,60 na RRDP 0,62. RRDP kuwa na higher delay kuliko Flooding katika high traffic inaelezwa kwa baadhi ya packets kusuppressiwa na hivyo kuzalisha new Interest packets na retransmissions.

Total packet volume katika network

Total number ya Interest na Data packets ni indirect indicator ya communication load ya network. Flooding ilizalisha highest packet volume kwa sababu inaruhusu nodes zote kubroadcast packets. RIF ilionyesha lowest packet counts kwa sababu inapunguza non-target regions na duplicate local forwarding.

Values katika table zimesomwa takribani kutoka kwenye graphs. Utafiti hautoi exact raw counts za results hizi katika separate data table.

Nini kilitokea idadi ya command-center regions ilipoongezeka?

Katika topology ya pili ya metres 1500 × 1500, network iligawanywa katika consumer regions moja, mbili, tatu na nne. Kuongezeka kwa idadi ya command centers kuliwezesha kila consumer kukusanya data kutoka producers katika smaller region na kupunguza average forwarding path lengths.

Successful packet acquisition ratio ya RIF iliongezeka kutoka karibu 0,85 katika configuration ya consumer mmoja na producers 75 hadi karibu 0,91 katika configuration ya consumers wanne na producers 18 kwa region. Average delay ilishuka kutoka karibu sekunde 0,75 hadi 0,47. Katika comparison hiyo hiyo, Interest packet count ya RIF ilishuka kutoka karibu 260.000 hadi 180.000, na Data packet count kutoka karibu 180.000 hadi 120.000.

Katika Flooding, BPF na RRDP, kuongezeka kwa consumer regions hakukuleta decrease kubwa sawa katika Interest packet count. Sababu ni kwamba methods hizi hazipunguzi moja kwa moja unnecessary inter-region circulation ya Interest packets.

Nguvu za utafiti ni zipi?

• Unatenganisha forwarding kwenda wrong region na local duplicate forwarding, na kushughulikia inefficiencies mbili katika architecture moja.
• Unalenga kujifunza region-location information kupitia existing Interest na Data packets bila periodic Hello messages.
• Unaunganisha location, remaining energy na neighbor-transmission count katika forwarding decision moja.
• Unatathmini method si dhidi ya Flooding pekee, bali pia dhidi ya BPF, RRDP na E-GIF.
• Unatumia scenarios mbili tofauti: increasing traffic load na changing number of command-center regions.
• Unawasilisha performance metrics nyingi pamoja: success ratio, delay, Interest packet volume na Data packet volume.

Mapungufu ya utafiti ni yapi?

• Utafiti huu ni preprint ambayo haijapitia peer review.
• Results zote zinategemea ndnSIM simulation; hakuna real UAV flight, field test au disaster drill.
• UAV zimemodelliwa katika fixed positions na same altitude. Wind, GPS error, position drift, battery replacement na dynamic repositioning hazijatathminiwa.
• Temporary link failures, asymmetric links, shadowing, multipath propagation na realistic fading conditions hazijajaribiwa.
• Ingawa energy-aware method inapendekezwa, total energy consumption, network lifetime au battery depletion per UAV havijaripotiwa kama outcome metrics.
• Timer parameters kama T_max, E_min na initial energy hazijaonyeshwa katika simulation-configuration table.
• Ingawa marudio ishirini ya simulations yameripotiwa, graphs hazina error bars, standard deviations, confidence intervals au statistical significance tests.
• RLT staleness, update cost, initial learning time na rebuilding after node changes hazijajaribiwa quantitatively.
• Byte overhead ya fields zilizoongezwa kwenye packet headers na effect yake kwenye low-bandwidth links haijaripotiwa.
• Security issues kama authentication ya region na coordinate information, malicious nodes au false location reporting hazijatathminiwa.
• Kuna unresolved interpretive difference kati ya altitude-selection graph na maelezo ya “near-maximum coverage”.
• Kuna transition isiyoelezwa kati ya timer formulas mbili kwa upande wa scale na units.

Utafiti unaunga mkono nini?

Simulation results zinaunga mkono kwamba chini ya fixed topologies na traffic conditions zilizochunguzwa, region-based forwarding pamoja na probabilistic suppression zinaweza kupunguza packet load, kuongeza data-acquisition ratio na kupunguza delay. RIF imeonyesha performance curve yenye robustness zaidi kuliko methods nne zilizolinganishwa, hasa packet sending rate inapoongezeka.

Utafiti hauthibitishi nini?

• Hauthibitishi kwamba RIF itatoa performance ile ile katika real disaster field.
• Hauthibitishi kwamba RIF ni best method kwa UAV hardware zote, radio technologies zote na terrain conditions zote.
• Hauonyeshi kwamba proposed method huongeza UAV battery life kwa percentage fulani.
• Hauonyeshi reliability ya RIF katika mobile UAV networks, dense urban environments au severe interference.
• Hautoi mafanikio ya integration na real disaster-management agencies, scaling, regulatory compliance au operational safety.
• Simulation graphs peke yake hazithibitishi kwamba differences kati ya methods ni statistically significant.

Umuhimu kwa mtazamo wa zamani, sasa na baadaye

Previous forwarding approaches kwa kawaida zililenga kusuppress local packet copies au kuamua direction ya target kwa location information. RIF inaunganisha geographic regional restriction na probabilistic forwarding inayotegemea energy na neighborhood state, hivyo kuleta approaches hizi mbili katika design moja.

Mchango wa sasa ni kutoa practical protocol draft na comparative simulation evidence inayoweza kupunguza communication load katika controlled networks zenye fixed-position UAV relays. Approach hii ina technical research value hasa kwa temporary communication systems ambazo hazina centralized infrastructure.

Katika future, experiments zinahitajika zenye realistic radio channels, limited position drift, temporary link losses, moving disaster hotspots na dynamic regional boundaries. Watafiti pia wanapendekeza limited movement ndani ya radius ya metres 50, 3GPP urban microcell channel models na resizing regions kulingana na changing disaster demand kama future work.

Mbinu na Matokeo ya Utafiti

Methodological summary

Simulation groups

• Proposed method: RIF.
• Comparison methods: Flooding, BPF, RRDP na E-GIF.
• Simulator: ndnSIM na NS-3.
• Wireless technology: IEEE 802.11b.
• UAV altitude: Metres 170.
• Communication range: Metres 200.
• Simulation duration: Sekunde 300.
• Number of repeats: 20.
• Scenario ya kwanza: Interest packets 1–8 kwa sekunde na consumer region moja.
• Scenario ya pili: Interest packet 1 kwa sekunde na consumer regions 1–4.

Measured outcome variables

• Successful packet acquisition ratio.
• Average Data packet acquisition delay, seconds.
• Total Interest packets transmitted in the network.
• Total Data packets transmitted in the network.

Main comparative findings

• Kadiri Interest packet sending rate ilivyoongezeka, acquisition ratio ya methods zote ilipungua huku delay na packet volume zikiongezeka.
• RIF ilionyesha highest successful acquisition ratio katika traffic rates zote zilizotathminiwa.
• RIF ilionyesha lowest average acquisition delay katika traffic rates zote zilizotathminiwa.
• Total Interest na Data packet volume ya RIF ilikuwa lower kuliko methods nne zilizolinganishwa.
• Kadiri idadi ya consumer regions ilivyoongezeka, forwarding paths zilipungua, success ratio ikaongezeka na delay ikapungua.
• Kuongezeka kwa regions kulipunguza packet volume kwa uwazi zaidi katika RIF na E-GIF, huku Interest packet count ikibaki high katika Flooding, BPF na RRDP.

Statistical evaluation

Utafiti unaripoti simulations zilirudiwa mara 20. Hata hivyo, random seeds zilizotumika, method ya averaging results, standard deviation, standard error, confidence interval, effect size au hypothesis test hazijaripotiwa. Kwa kuwa graphs hazina error bars, magnitude ya apparent differences kati ya methods haiwezi kutathminiwa dhidi ya variability kati ya repeats.

Dokezo la Chanzo na Mbinu

Jina asili la utafiti: Regional Interest Forwarding for NDN-Based UAV Relays in Emergency Response Networks

Waandishi: Wuyungerile Li; Jia Xuan Lv; Qian Qian Chen; Jian Guo; Alvin Valera; Winston K.G. Seah.

Mpangilio wa waandishi: Umehifadhiwa kama ulivyo katika utafiti uliopakiwa.

Equal first author: Equal contribution au equal first authorship haijaelezwa.

Corresponding author: Wuyungerile Li.

Taasisi: Department of Computer Science, Inner Mongolia University, Hohhot, Inner Mongolia, China; School of Engineering and Computer Science, Victoria University of Wellington, Wellington, New Zealand.

DOI:10.2139/ssrn.6902578

Peer-reviewed journal: Hakuna taarifa ya peer-reviewed journal kwa version hii.

Publication platform: SSRN.

Original publisher: Hakuna peer-reviewed journal publisher kwa version hii. SSRN ni preprint na early-research platform ya Elsevier; SSRN si academic publisher wala peer-reviewed journal.

Publication year na submission date: 2026; ilichapishwa kwenye SSRN tarehe 9 Juni 2026.

Aina ya chanzo: Preprint ambayo haijapitia peer review; network-protocol design na simulation study.

Peer-review status: Utafiti huu ni preprint na haujapitia peer review.

Chanzo rasmi:Ukurasa rasmi wa utafiti wa SSRN

Support information: Utafiti uliungwa mkono na project number 2025KJHZ0028 yenye jina “Research on the Reliability of 6G Mobile Edge Computing Networks” chini ya Key Research of Development and Achievement Transformation Project ya Inner Mongolia Autonomous Region.

Maelezo haya ya Kiswahili yameandaliwa kwa kuchunguza full text, formulas, tables, network topologies, flowcharts na performance graphs zote katika utafiti uliopakiwa. External sources zilitumika tu kwa bibliographic verification ya authors, DOI, publication date, platform na peer-review status; hakuna scientific findings zisizokuwapo katika utafiti zilizoongezwa.

Main limitations za utafiti ni kutegemea simulation pekee, kutumia fixed UAV topology, kutokujaribu realistic mobility na radio-channel degradation, kutopima energy consumption moja kwa moja, kutoeleza baadhi ya timer parameters na kutotoa variability au statistical-significance measures kwa results. Kwa hiyo findings hazipaswi kutafsiriwa kama communication success iliyothibitishwa katika real disaster field.