Agent Distributed Computing: Leader Election and Minimum Spanning Tree Algorithms

Contents

• 1. Gabatarwa
• 2. Tushen Samfurin Hankali
  • 2.1 Kwatanta Model
  • 2.2 Bambance-bambance Masu Muhimmanci
• 3. Algorithm na Zaben Shugaba
  • 3.1 情形 k < n
  • 3.2 Yanayin k = n
• 4. Gina Bishiyar Tsiron Zaitun
• 5. Binciken Fasaha
  • 5.1 Tsarin Lissafi
  • 5.2 Sakamakon Gwaji
• 6. Misalin Tsarin Bincike
• 7. Aikace-aikace da Shigowa na Gaba
• 8. References

1. Gabatarwa

Tsarin lissafi na rarrabawa na Agent yana faɗaɗa tsarin watsa saƙo na al'ada ta hanyar gabatar da na'urar lissafi mai motsi (Agent) wanda zai iya ƙaura tsakanin nodes. Wannan maƙala ta fara nazari cikakke game da ikon Agent k ≤ n don aiwatar da ayyukan matakin jadawali a cikin wannan samfurin, yana ba da ingantattun mafita na lokacin aiki da ƙaramin ƙwaƙwalwar ajiya don matsalar zaɓen shugabanci da gina bishiyar mafi ƙanƙanta.

2. Tushen Samfurin Hankali

The agent model represents a paradigm shift from static computing devices to mobile computing devices, where agents must communicate through physical migration rather than sending messages via fixed links.

2.1 Kwatanta Model

Table 1 compares the fundamental characteristics of the message-passing model and the agent model:

2.2 Bambance-bambance Masu Muhimmanci

The agent model introduces two major differences: (1) computing devices are mobile rather than static; (2) communication requires physical migration to the same node rather than message transmission.

3. Algorithm na Zaben Shugaba

This paper proposes two deterministic leader election algorithms optimized for different agent-node ratios.

3.1 情形 k < n

Don yanayin adadin wakilai ya kasa na'urori, algorithm ɗin ya cimma lokacin aiki na $O(D + \sqrt{n})$ (inda D ke nufin diamita na jadawali), an inganta ƙarfin ƙwaƙwalwar ajiya don ƙuntatawa na wakilan motsi.

3.2 Yanayin k = n

When each node contains an agent, this algorithm builds upon prior work disclosed at DISC 2024, achieving optimal $O(D)$ time complexity.

4. Gina Bishiyar Tsiron Zaitun

Using the outcome of leader election, the authors developed a deterministic algorithm that enables agents to construct the graph's minimum spanning tree. This approach minimizes both time and memory complexity while adapting traditional MST algorithms (such as Borůvka or Prim's algorithm) to the constraints of the agent model.

5. Binciken Fasaha

5.1 Tsarin Lissafi

Agent model can be formally defined as tuple $G = (V, E, A)$, where V represents nodes, E represents edges, A represents mobile agents. Communication constraints require agents $a_i$ and $a_j$ must coexist at certain node $v \in V$ to exchange information, which fundamentally alters cost model of message passing.

5.2 Sakamakon Gwaji

Duk da hankalin ka'idar wannan rubutun, amma waɗannan algorithms sun nuna ingantaccen ci gaba a amfani da ƙwaƙwalwa idan aka kwatanta da hanyoyin gargajiya. Sakamakon lokacin sarƙaƙiya ya nuna, ko da yake akwai ƙuntataccen sadarwa, algorithms na wakili na iya cimma aikin da ya yi daidai da na algorithms watsa saƙo a kan matsalolin zane na asali.

6. Misalin Tsarin Bincike

Babban hasashe:Agent model ba wani bara ne na ilimi kawai ba – yana da wani tushe na sake tunani game da lissafi mai rarrabawa, yana nuna yadda tsarin duniya na zahiri (kamar hanyoyin sadarwa na mutum-mutumi da na'urorin Intanet) ke sadarwa ta hanyar motsi. Idan aka kwatanta da hasashen hanyar sadarwa ta al'ada, wannan yana ba da ƙarin samfuri na gaske ga sabon tsarin lissafi na gefe.

Logical Context:Wannan labarin ya fara ne daga tushen ka'idar kafa samfurin, sannan ya bi ta matakai don warware matsalolin asali na zane, ta hanyar tsari mai tsauri. Ci gaba daga zaɓen shugaba zuwa gina MST yana nuna yadda ainihin kalmomi ke tallafawa ayyuka masu rikitarwa, wanda yayi kama da ci gaban hanyoyin lissafi na rarrabawa na al'ada.

Ribobi da Rashin isa:主要优势在于解决了k < n这一实际约束，反映了并非每个节点都具备计算能力的真实部署场景。然而，同步假设和无限制本地计算是显著局限——真实移动系统面临异步操作和计算约束。与革命性领域转换的CycleGAN论文（Zhu等，2017）等开创性工作相比，本研究奠定了理论基础但缺乏实证验证。

Shawarwari masu yuwuwa:Masu bincike ya kamata su fadada wadannan sakamako zuwa tsarin da bai zama na lokaci-lokaci ba, kuma su tabbatar da su a cikin dandamali na gwaji na zahiri. Masu aiki a masana'antar robotics da Internet of Things lokacin tsara tsarin da ke bukatar sadarwa ta kusanci ta zahiri, ya kamata su yi la'akari da samfurin agent, saboda yana ba da madaidaicin iyaka mai sarƙaƙƙiya fiye da samfurin al'ada.

7. Aikace-aikace da Shigowa na Gaba

Samfurin agent yana da babban yuwuwar fage da yawa:

• Botnet:A cikin tsarin gungun na'urorin mutum-mutumi, na'urorin suna buƙatar saduwa a zahiri don musayar bayanai
• Edge Computing:Na'urar gefen wayoyi masu motsi waɗanda ke sadarwa ta kusanci na jiki
• Amsar bala'i:Cibiyar sadarwa ta gaggawa tare da lalata kayan aiki
• Binciken sararin samaniya:Rover ɗin Duniya Wanda Yake Aiwatar da Canja Bayanan Bayanai Ta Hanyar Haɗuwa

Bincike na gaba ya kamata ya mayar da hankali kan faɗaɗa samfurin zuwa saitunan da ba na lokaci-lokaci ba, haɗa ƙayyadaddun makamashi, da haɓaka algorithms don ayyuka masu rikitarwa fiye da zaɓen shugaba da MST.

8. References

1. Kshemkalyani, A. D., Kumar, M., Molla, A. R., & Sharma, G. (2024). 简要公告：智能体分布式计算. DISC 2024会议论文集.
2. Zhu, J. Y., Park, T., Isola, P., & Efros, A. A. (2017). 使用循环一致对抗网络的无配对图像到图像转换. IEEE国际计算机视觉会议论文集.
3. Lynch, N. A. (1996). Distributed Algorithms. Morgan Kaufmann Publishers.
4. Peleg, D. (2000). Distributed Computing: A Locality-Sensitive Approach. Society for Industrial and Applied Mathematics.